org-id: biit_cs_ut_ee
org-fn: BIIT Group, Institute of Computer Science
org-url: http://biit.cs.ut.ee
org-inst: University of Tartu
org-inst-url: http://ut.ee
org-locality: Tartu
org-country: Estonia

org-id: bioinfo_cipf_es
org-fn: Bioinformatics Department
org-url: http://bioinfo.cipf.es
org-inst: Centro de Investigacion Principe Felipe
org-locality: Valencia
org-country: Spain

org-id: bioinfo_unice_fr
org-fn: Virtual Biology Lab
org-url: http://bioinfo.unice.fr
org-inst: Institute of Signaling, Developmental Biology and Cancer Research
org-locality: Nice
org-country: France

org-id: bioinformatics_clemson
org-fn: Clemson Bioinformatics Center
org-url: http://bioinformatics.clemson.edu
org-region: South Carolina
org-country: USA

org-id: bioinformatics_nyu
org-fn: NYU Bioinformatics Group
org-url: http://bioinformatics.nyu.edu
org-locality: New York
org-region: New York
org-country: USA

org-id: bioinfow_dep_usal_es
org-fn: Bioinformatics and Functional Genomics Research Group
org-url: http://bioinfow.dep.usal.es
org-inst: Cancer Research Center
org-locality: Salamanca
org-country: Spain

org-id: bmir_stanford
org-fn: Stanford Center for Biomedical Informatics Research
org-url: http://bmir.stanford.edu
org-inst: Stanford University
org-inst-url: http://stanford.edu
org-region: California
org-country: USA

org-id: cpc_busm
org-fn: Cardiovascular Proteomics Center
org-url: http://www.bumc.bu.edu/cardiovascularproteomics/
org-inst: Boston University School of Medicine
org-inst-url: http://www.bumc.bu.edu/busm/
org-locality: Boston
org-region: Massachusetts
org-country: USA

org-id: campus_usal_es
org-fn: Universidad de Salamanca
org-url: http://campus.usal.es/web-usal/Ingles/index.html
org-locality: Salamanca
org-country: Spain

org-id: cancer_ucsf
org-fn: UCSF Helen Diller Family Comprehensive Cancer Center Biostatistics and Computational Biology Core
org-url: http://cancer.ucsf.edu/biostat/index.php
org-region: California

org-id: cchmc
org-fn: Cincinnati Childrens Hospital Medical Center
org-url: http://www.cincinnatichildrens.org/research/
org-locality: Cincinnati
org-region: Ohio
org-country: USA

org-id: cgap
org-fn: Cancer Genome Anatomy Project
org-url: http://cgap.nci.nih.gov

org-id: biowww_washington
org-fn: Department of Biochemistry
org-url: http://depts.washington.edu/biowww
org-inst: University of Washington

org-id: ecoliwiki
org-fn: EcoliWiki
org-url: http://ecoliwiki.org

org-id: estbioinfo_stat_ub_es
org-fn: Statistics and Bioinformatics Research Group
org-url: http://estbioinfo.stat.ub.es/estbioinfo/index.htm
org-inst: University of Barcelona

org-id: fields_scripps
org-fn: Yates Lab at the Scripps Research Institute
org-url: http://fields.scripps.edu
org-locality: La Jolla
org-region: California
org-country: USA

! org-id: franklin_imgen_bcm_tmc
! org-fn: Baylor College of Medicine
! org-url: http://franklin.imgen.bcm.tmc.edu

org-id: gauss_dbb_georgetown
org-fn: Georgetown University Medical Center Liu Lab
org-url: http://gauss.dbb.georgetown.edu/liblab

org-id: gdm_fmrp_usp_br
org-fn: Molecular Genetics and Bioinformatics Laboratory
org-url: http://gdm.fmrp.usp.br
org-inst: University of Sao Paolo
org-country: Brazil

org-id: genemania_team
org-fn: GeneMania team: Bader and Morris labs
org-url: http://genemania.org/pages/people.jsf
org-inst: University of Toronto
org-inst-url: http://www.utoronto.ca
org-locality: Toronto
org-country: Canada

org-id: gst_ornl
org-fn: Oak Ridge National Laboratory (ORNL)
org-url: http://gst.ornl.gov

org-id: gst_tennessee
org-fn: University of Tennessee Genome Science and Technology
org-url: http://gst.tennessee.edu
org-region: Tennessee

org-id: llama_med_harvard
org-fn: Roth lab
org-url: http://llama.med.harvard.edu
org-inst: Harvard Medical School

org-id: mcbc_usm
org-fn: Mississippi Computational Biology Consortium
org-url: http://mcbc.usm.edu

org-id: mips_helmholtz_muenchen_de
org-fn: The Institute of Bioinformatics and Systems Biology (IBIS)
org-url: http://mips.helmholtz-muenchen.de
org-inst: Helmholtz Zentrum München
org-locality: Munich
org-country: Germany

org-id: molgen_biol_rug_nl
org-fn: Groningen Biomolecular Sciences and Biotechnology Institute
org-url: http://molgen.biol.rug.nl/molgen/index.php
org-locality: Haren
org-country: the Netherlands

org-id: pathcuric1_swmed
org-fn: Department of Pathology
org-url: http://pathcuric1.swmed.edu
org-inst: University of Tennessee Southwestern Medical Center

org-id: smd_stanford
org-fn: Stanford Microarray Database
org-url: http://smd.stanford.edu

org-id: spotfire_tibco
org-fn: Spotfire, Inc.
org-url: http://spotfire.tibco.com

org-id: nagrp
org-fn: US National Animal Genome Research Program
org-url: http://www.animalgenome.org
org-locality: Ames
org-region: Iowa
org-country: USA

org-id: tair
org-fn: The Arabidopsis Information Resource
org-url: http://www.arabidopsis.org

org-id: berkeleybop
org-fn: Berkeley Bioinformatics Open-Source Projects
org-url: http://www.berkeleybop.org
org-inst: Lawrence Berkeley National Lab
org-inst-url: http://www.lbl.gov
org-locality: Berkeley
org-region: California
org-country: USA

org-id: bioconductor
org-fn: BioConductor
org-url: http://www.bioconductor.org

org-id: bioperl
org-fn: Open-Bio
org-url: http://www.bioperl.org

org-id: biotec_tu_dresden_de
org-fn: Biotechnological Centre
org-url: http://www.biotec.tu-dresden.de
org-inst: Technological University
org-locality: Dresden
org-country: Germany

org-id: bork_embl_de
org-fn: Bork group
org-url: http://www.bork.embl-heidelberg.de
org-inst: European Molecular Biology Laboratory
org-inst-url: http://www.embl-heidelberg.de

org-id: ccbb
org-fn: Center for Computational Biology and Bioinformatics
org-url: http://www.c2b2.columbia.edu
org-inst: Columbia University

org-id: charite_de
org-fn: Charité University Hospital
org-url: http://www.charite.de
org-country: Germany

org-id: cicancer
org-fn: Centro de Investigacion del Cancer
org-url: http://www.cicancer.org
org-locality: Salamanca
org-country: Spain

org-id: cmu
org-fn: Carnegie Mellon University
org-url: http://www.cmu.edu
org-locality: Pittsburgh
org-region: Pennsylvania
org-country: USA

org-id: cnb_csic
org-fn: National Center of Biotechnology (CNB-CSIC)
org-url: http://www.cnb.csic.es
org-locality: Madrid
org-country: Spain

org-id: columbia
org-fn: Columbia University
org-url: http://www.columbia.edu

org-id: compbio_dundee_ac_uk
org-fn: Barton group
org-url: http://www.compbio.dundee.ac.uk
org-inst: University of Dundee

org-id: cos_ufrj_br
org-fn: Systems Engineering and Computer Science Program
org-url: http://www.cos.ufrj.br

org-id: crc_jussieu_fr
org-fn: Centre de Recherche des Cordeliers
org-url: http://www.crc.jussieu.fr/crc/index.php?lang=en
org-locality: Paris
org-country: France

org-id: cs_man_ac_uk
org-fn: University of Manchester
org-url: http://www.cs.man.ac.uk

org-id: custom_microsystems
org-fn: Custom Microsystems
org-url: http://www.dbfordummies.com/ContactInfo.asp

org-id: ebi
org-fn: European Bioinformatics Institute
org-url: http://www.ebi.ac.uk
org-locality: Cambridge
org-country: UK

org-id: rebholz_at_ebi
org-fn: Rebholz group
org-url: http://www.ebi.ac.uk/Rebholz
org-inst: European Bioinformatics Institute
org-inst-url: http://www.ebi.ac.uk

org-id: embl
org-fn: European Molecular Biology Laboratory
org-url: http://www.embl-heidelberg.de

org-id: uni_amsterdam
org-fn: University of Amsterdam
org-url: http://www.english.uva.nl
org-country: Holland

org-id: genetics_ac_cn
org-fn: Institute of Genetics and Developmental Biology, Chinese Academy of Sciences
org-url: http://www.genetics.ac.cn

org-id: genomics_org_cn
org-fn: Beijing Genomics Institute
org-url: http://www.genomics.org.cn
org-country: China

org-id: gladstone_institutes
org-fn: Gladstone Institutes
org-url: http://www.gladstone.ucsf.edu
org-inst: University of California

org-id: gripstudios
org-fn: Grip Studios Interactive, Inc.
org-url: http://www.gripstudios.com

org-id: hsph
org-fn: Harvard School of Public Health
org-url: http://www.hsph.harvard.edu

org-id: castillo_lab
org-fn: Castillo-Davis Laboratory
org-url: http://cdl.cbcb.umd.edu
org-inst: University of Maryland
org-inst-url: http://www.umd.edu
org-region: Maryland
org-country: USA

org-id: huji
org-fn: The Hebrew University of Jerusalem
org-url: http://www.huji.ac.il
org-country: Israel

org-id: iastate
org-fn: Iowa State University
org-url: http://www.iastate.edu

org-id: ibdm_univ_mrs_fr
org-fn: Developmental Biology Institute of Marseille
org-url: http://www.ibdm.univ-mrs.fr
org-country: France

org-id: ici_upmc_fr
org-fn: INSERM U872 Integrative Cancer Immunology Team 15
org-url: http://www.ici.upmc.fr
org-inst: Cordelier Research Center
org-locality: Paris
org-country: France

org-id: iis_sinica_edu_tw
org-fn: Institute of Information Science
org-url: http://www.iis.sinica.edu.tw/index.htm
org-inst: Academia Sinica
org-country: Taiwan

org-id: illuminae
org-fn: Illuminae
org-url: http://www.illuminae.com

org-id: imb_uq_edu_au
org-fn: Institute for Molecular Bioscience
org-url: http://www.imb.uq.edu.au
org-region: Queensland
org-country: Australia

org-id: mgi
org-fn: Mouse Genome Informatics
org-url: http://www.informatics.jax.org
org-locality: Bar Harbor
org-region: Maine
org-country: USA

org-id: inserm
org-fn: Institut National de la Santé et de la Recherche Medicale
org-url: http://www.inserm.fr/en
org-inst: Centre de Recherche des Cordeliers
org-inst-url: http://www.crc.jussieu.fr/crc/index.php?lang=en
org-locality: Paris
org-country: France

org-id: ir_vhebron_net
org-fn: Statistics and Bioinformatics Unit, Institut de Recerca Hospital Universitari Vall d'Hebron
org-url: http://www.ir.vhebron.net/easyweb_irvh/Serveis/UEB/tabid/792/Default.aspx

org-id: ism_ac_jp
org-fn: Institute of Statistical Mathematics, Research Organization of Information and Systems
org-url: http://www.ism.ac.jp/index_e.html
org-country: Japan

org-id: ibrb_nhrf
org-fn: Metabolic Engineering and Bioinformatics Group, Institute of Biological Research and Biotechnology
org-url: http://www.eie.gr/nhrf/institutes/ibrb/programmes/metabolicengineering-en.html
org-inst: National Hellenic Research Foundation
org-inst-url: http://www.eie.gr/index-en.html
org-locality: Athens
org-country: Greece

org-id: izbi_de
org-fn: Interdisciplinary Centre for Bioinformatics
org-url: http://www.izbi.de
org-inst: University of Leipzig
org-country: Germany

org-id: jcvi
org-fn: The J. Craig Venter Institute
org-url: http://www.jcvi.org

org-id: kuleuven_be
org-fn: Bioinformatics group
org-url: http://www.kuleuven.be/bioinformatics
org-inst: ESAT / K. U. Leuven
org-country: Belgium

org-id: mdibl
org-fn: Mount Desert Island Biological Laboratory
org-url: http://www.mdibl.org
org-region: Maine
org-country: USA

org-id: medinfopoli_polimi_it
org-fn: Bio-Medical Informatics Laboratory
org-url: http://www.medinfopoli.polimi.it
org-inst: Politecnico di Milano
org-locality: Milan
org-country: Italy

org-id: molgen_mpg
org-fn: Max Planck Institute for Molecular Genetics
org-url: http://www.molgen.mpg.de
org-locality: Berlin
org-country: Germany

org-id: niaid_nih
org-fn: National Institute of Allergy and Infectious Diseases
org-url: http://www.niaid.nih.gov
org-locality: Bethesda
org-region: Maryland
org-country: USA

org-id: nlm_nih
org-fn: National Library of Medicine
org-url: http://www.nlm.nih.gov

org-id: ntnu_no
org-fn: Norwegian University of Science and Technology
org-url: http://www.ntnu.no
org-locality: Trondheim
org-country: Norway

org-id: twigger_lab
org-fn: Twigger Lab
org-url: http://www.phys.mcw.edu/fac_twigger.htm
org-inst: Medical College of Wisconsin

org-id: polimi_it
org-fn: Politecnico di Milano
org-url: http://www.polimi.it

org-id: psb_ugent_be
org-fn: Department of Plant Systems Biology
org-url: http://www.psb.ugent.be
org-inst: VIB / Ghent University
org-inst-url: http://www.ugent.be/en
org-locality: Ghent
org-country: Belgium

org-id: seqexpress
org-fn: SeqExpress
org-url: http://www.seqexpress.com

org-id: snubi
org-fn: Seoul National University Biomedical Informatics
org-url: http://www.snubi.org

org-id: strandgenomics
org-fn: Strand Genomics
org-url: http://www.strandgenomics.com

org-id: tm4
org-fn: DFCI, JCVI, and the University of Washington
org-url: http://www.tm4.org

org-id: uc_madrid
org-fn: Universidad Complutense de Madrid
org-url: http://www.ucm.es
org-locality: Madrid
org-country: Spain

org-id: ucr
org-fn: University of California, Riverside
org-url: http://www.ucr.edu

org-id: uni_navarra
org-fn: University of Navarra
org-url: http://www.unav.es
org-country: Spain

org-id: unice_fr
org-fn: Institute of Signaling, Developmental Biology and Cancer Research
org-url: http://www.unice.fr/isdbc
org-locality: Nice
org-country: France

org-id: usm
org-fn: University of Southern Mississippi
org-url: http://www.usm.edu
org-region: Mississippi

org-id: utmem
org-fn: University of Tennessee Health Science Center
org-url: http://www.utmem.edu

org-id: utoronto
org-fn: University of Toronto
org-url: http://www.utoronto.ca/
org-locality: Toronto
org-country: Canada

org-id: wehi
org-fn: Walter and Eliza Hall Institute of Medical Research
org-url: http://www.wehi.edu.au
org-locality: Melbourne
org-country: Australia

org-id: xspan
org-fn: XSPAN project
org-url: http://www.xspan.org
org-inst: University of Edinburgh
org-country: UK

org-id: sgd
org-fn: Saccharomyces Genome Database
org-url: http://www.yeastgenome.org

org-id: fc_ul
org-fn: Faculty of Sciences
org-url: http://xldb.fc.ul.pt
org-inst: University of Lisbon
org-inst-url: http://www.ul.pt
org-locality: Lisbon
org-country: Portugal

org-id: ycmi
org-fn: Yale Center for Medical Informatics
org-url: http://ycmi.med.yale.edu

org-id: agbase
org-fn: AgBase
org-inst: Mississippi State University
org-url: http://agbase.msstate.edu
org-inst-url: http://www.msstate.edu
org-locality: Starkville
org-region: Mississippi
org-country: USA

org-id: agilent_labs_tel_aviv
org-fn: Agilent Labs Tel-Aviv
org-url: http://www.agilent.com/labs
org-locality: Tel-Aviv
org-country: Israel

org-id: bioinformatics_center_china_agricultural_university
org-fn: Bioinformatics Center
org-inst: China Agricultural University
org-url: http://bioinformatics.cau.edu.cn
org-inst-url: http://www.cau.edu.cn
org-locality: Beijing
org-country: China

org-id: mpi_inf_mpg_de
org-fn: Department of Computational Biology and Applied Algorithmics
org-inst: Max Planck Institute for Informatics
org-url: http://www.mpi-inf.mpg.de/departments/d3/index.html
org-inst-url: http://www.mpi-inf.mpg.de/
org-locality: Saarbrucken
org-country: Germany

org-id: fda_nctr
org-fn: National Center for Toxicological Research (NCTR)
org-url: http://www.fda.gov/AboutFDA/CentersOffices/nctr/default.htm
org-inst: Food and Drug Administration
org-inst-url: http://www.fda.gov
org-locality: Jefferson
org-region: Arkansas
org-country: USA

org-id: bejerano_stanford
org-fn: Bejerano Lab
org-url: http://bejerano.stanford.edu
org-inst: Stanford University
org-inst-url: http://stanford.edu
org-locality: Stanford
org-region: California
org-country: USA

org-id: discover_nci_nih
org-fn: Genomics and Bioinformatics Group
org-inst: NIH National Cancer Institute
org-url: http://discover.nci.nih.gov
org-inst-url: http://www.nci.nih.gov
org-locality: Bethesda
org-region: Maryland
org-country: USA

org-id: goc
org-fn: GO Consortium
org-url: http://www.geneontology.org

org-id: vortex_cs_wayne
org-fn: Intelligent Systems and Bioinformatics Laboratory
org-inst: Wayne State University
org-url: http://vortex.cs.wayne.edu
org-inst-url: http://wayne.edu
org-locality: Detroit
org-region: Michigan
org-country: USA

org-id: genomics_princeton
org-fn: Lewis-Sigler Institute for Integrative Genomics
org-inst: Princeton University
org-url: http://genomics.princeton.edu
org-inst-url: http://princeton.edu
org-locality: Princeton
org-region: New Jersey
org-country: USA

org-id: ntnu
org-fn: Norwegian University of Science and Technology (NTNU)
org-url: http://www.semantic-systems-biology.org
org-locality: Trondheim
org-country: Norway

org-id: rudjer_boskovic_institute
org-fn: Rudjer Boskovic Institute
org-url: http://www.irb.hr/en
org-locality: Zagreb
org-country: Croatia

org-id: technion_laboratory_of_computational_biology
org-fn: Technion Laboratory of Computational Biology
org-url: http://bioinfo.cs.technion.ac.il
org-locality: Haifa
org-country: Israel

org-id: uniprotkb_goa
org-fn: UniProtKB-GOA
org-inst: European Bioinformatics Institute
org-inst-url: http://www.ebi.ac.uk
org-url: http://www.ebi.ac.uk/GOA
org-locality: Cambridge
org-country: UK

id: avadis
name: Avadis
url: http://avadis.strandgenomics.com
dev_id: strandgenomics
tool_type: statistical
platform: linux
platform: mac
platform: win
description: Avadis is a data analysis and visualization tool for gene expression data. Avadis has a built-in Gene Ontology browser to view ontology hierarchies. There are common ontology paths for multiple genes. Genes can be clustered based on ontology terms to identify functional signatures in gene expression clusters.
license: proprietary

id: apid
name: Agile Protein Interaction Data Analyzer
name_acronym: APID
url: http://bioinfow.dep.usal.es/apid/index.htm
dev_id: bioinfow_dep_usal_es
tool_type: other_analysis
tool_type_other: protein-protein interaction analysis
platform: web
pub_pmid: 16845013
description: Agile Protein Interaction Data Analyzer is an interactive bioinformatics web tool developed to integrate and analyze in a unified and comparative platform main currently known information about protein-protein interactions demonstrated by specific small-scale or large-scale experimental methods. At present, the application includes information coming from five main source databases enclosing an unified sever to explore more than 40000 different proteins and close to 150000 different proven interactions. The website includes search tools to query and browse upon the data, allowing selection of the interaction pairs based in calculated parameters that weight and qualify the reliability of each given protein interaction. Parameters for the proteins are connectivity, cluster coefficient, Gene Ontology (GO) functional environment, GO environment enrichment; for the interactions: number of methods, GO overlapping, Pfam domain-domain interaction. APID also includes a graphic interactive tool to visualize selected sub-networks and to navigate on them or along the whole interaction network.
license: free_academic

id: agrigo
name: agriGO
url: http://bioinfo.cau.edu.cn/agriGO/index.php
contactemail: zhensu@cau.edu.cn
contactname: Zhen Su
dev_id: bioinformatics_center_china_agricultural_university
tool_type: browser
tool_type: database
tool_type: statistical
tool_type: term_enrichment
tool_type: text_mining
tool_type: visualization
platform: web
pub_pmid: 20435677
description: Gene Ontology (GO), the de facto standard in gene functionality description, is used widely in functional annotation and enrichment analysis. Here, we introduce agriGO, an integrated web-based GO analysis toolkit for the agricultural community, using the advantages of our previous GO enrichment tool (EasyGO), to meet analysis demands from new technologies and research objectives. EasyGO is valuable for its proficiency, and has proved useful in uncovering biological knowledge in massive data sets from high-throughput experiments. For agriGO, the system architecture and website interface were redesigned to improve performance and accessibility. The supported organisms and gene identifiers were substantially expanded (including 38 agricultural species composed of 274 data types). The requirement on user input is more flexible, in that user-defined reference and annotation are accepted. Moreover, a new analysis approach using Gene Set Enrichment Analysis strategy and customizable features is provided. Four tools, SEA (Singular enrichment analysis), PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (Transfer IDs by BLAST) and SEACOMPARE (Cross comparison of SEA), are integrated as a toolkit to meet different demands. We also provide a cross-comparison service so that different data sets can be compared and explored in a visualized way. Lastly, agriGO functions as a GO data repository with search and download functions; agriGO is publicly accessible at <a rel="external" href="http://bioinfo.cau.edu.cn/agriGO/">http://bioinfo.cau.edu.cn/agriGO/</a>.
open_source: false
go_data: term
go_data: def
go_data: rel
go_data: gp
go_data: ref
go_data_src: db
license: free_academic
update_frequency: weekly
submission_date: 2010-06-02 15:31:58
comments: The comments from Faculty of 1000 biology:<br>This paper describes a new bioinformatic resource that will be of great use to any plant scientist carrying out genomic studies.<br>agriGO provides an intuitive and relatively user-easy platform for carrying out Gene Ontology (GO) analyses of genomic data from over 30 plant species. The tools provided include Singular Enrichment Analysis (SEA), which analyses a simple gene list for GO enrichment, and Parametric Analysis of Gene Set Enrichment (PAGE), which takes expression levels into account when analyzing GO enrichment. The platform provides publication quality outputs.

id: amigo
name: AmiGO
url: http://amigo.geneontology.org/
contactemail: gohelp@geneontology.org
contactname: GO Helpdesk
dev_id: goc
tool_type: browser
tool_type: other_analysis
tool_type: search
tool_type: term_enrichment
tool_type: visualization
tool_type: slimmer
platform: web
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 19033274
description: AmiGO provides an interface to search and browse the ontology and annotation data provided by the GO consortium. Users can search for gene products and view the terms with which they are associated; alternatively, users can search or browse the ontology for GO terms of interest and see term details and gene product annotations. AmiGO also provides a BLAST search engine, which searches the sequences of genes and gene products that have been annotated to a GO term and submitted to the GO Consortium.</p><p>AmiGO accesses the GO mySQL database; more information is available from the <a href="GO.database.shtml" title="Documentation on the GO database">GO database guide</a>.
license: free_academic
open_source: true
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: subset
go_data: gp
go_data: ev_code
go_data: ref
go_data: qual
go_data: taxon
go_data_src: db
update_frequency: daily
submission_date: 2010-10-10 10:10:10

id: b2g
name: Blast2GO
name_abbr: B2G
url: http://www.blast2go.org
dev_id: bioinfo_cipf_es
tool_type: editor
tool_type: statistical
tool_type: slimmer
platform: linux
platform: mac
platform: unix
platform: win
pub_pmid: 16081474
description: Blast2GO joins in one universal application similarity search based GO annotation and functional analysis. B2G offers the possibility of direct statistical analysis on gene function information and visualization of relevant functional features on a highlighted GO direct acyclic graph (DAG). Furthermore B2G includes various statistics charts summarizing the results obtained at BLASTing, GO-mapping, annotation and enrichment analysis (Fisher's Exact Test). All analysis process steps are configurable and data import and export are supported at any stage. The application also accepts pre-existing BLAST or annotation files and takes them to subsequent steps. The tool offers a very suitable platform for high throughput functional genomics research in non-model species. B2G is a species-independent, intuitive and interactive desktop application which allows monitoring and comprehending the whole annotation and analysis process supported by additional features like GO Slim integration, evidence code (EC) consideration, a Batch-Mode or GO-Multilevel-Pies.
license: free_academic

id: bingo
name: BiNGO
url: http://www.psb.ugent.be/cbd/papers/BiNGO
dev_id: psb_ugent_be
contactname: Steven Maere
contactemail: steven.maere@psb.vib-ugent.be
tool_type: statistical
tool_type: term_enrichment
description: The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape's versatile visualization environment to produce an intuitive and customizable visual representation of the results.
license: free_academic
open_source: true
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 15972284
go_data: term
go_data: def
go_data: syn
go_data: rel
go_data: subset
go_data: gp
go_data: ev_code
go_data: qual
go_data: taxon
go_data_src: obo
go_data_src: gaf
go_data_src_other: NCBI, custom
update_frequency: no_fixed
submission_date: 2011-01-25 09:39:34

id: bioconduct
name: Bioconductor
url: http://bioconductor.org
dev_id: bioconductor
contactname: Bioconductor webmaster
contactemail: webmaster@bioconductor.org
tool_type: browser
tool_type: search
tool_type: visualization
tool_type: database
tool_type: software
tool_type: statistical
tool_type: term_enrichment
tool_type: text_mining
tool_type: other_analysis
tool_type_other: Flexible integration of GO into statistical analysis and comprehension of high-throughput genetic data.
description: Bioconductor provides tools for the analysis and comprehension of high-throughput (microarray, sequence, flow, etc.) genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. There are more than core and user-contributed 400 packages. Bioconductor packages the GO ontology into our semi-annual release, with software tools to: query; join with diverse additional gene, microarray, and sequence annotations; incorporate GO into annotation, differential expression, and gene set enrichment work flows; and visualize.
license: free_academic
open_source: true
platform: win
platform: mac
platform: unix
platform: linux
go_data: term
go_data: def
go_data: syn
go_data: rel
go_data: ev_code
go_data_src: db
go_data_src_other: Our users can easily obtain GO data from biomart, NCBI, uscs, ...
update_frequency: quarterly
submission_date: 2011-02-04 17:16:45

id: cgap_go_browser
name: CGAP GO browser
url: http://cgap.nci.nih.gov/Genes/GOBrowser
dev_id: cgap
tool_type: browser
platform: web
description: With the CGAP GO browser, you can browse through the GO vocabularies, and find human and mouse genes assigned to each term. <br>GO data updated every few months.
license: free_academic

id: bioperl
name: BioPerl
url: http://www.bioperl.org
dev_id: bioperl
tool_type: software
platform: linux
platform: mac
platform: unix
platform: win
description: BioPerl is a set of perl modules for use in bioinformatics. It includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies
license: free_academic

id: blip
name: Biomedical Logical Programming
name_abbr: Blip
url: http://www.blipkit.org
dev_id: berkeleybop
tool_type: software
platform: linux
platform: mac
platform: unix
platform: win
description: Biomedical Logical Programming is a research-oriented deductive database and prolog application library for handling biological and biomedical data. It includes packages for advanced querying of ontologies and annotations.<br>Blip underpins the Obol tool.
license: free_academic

id: categorizer
name: CateGOrizer
url: http://www.animalgenome.org/bioinfo/tools/catego/
contactemail: zhu@iastate.edu
contactname: Zhiliang Hu
dev_id: nagrp
tool_type: statistical
tool_type: slimmer
tool_type_other: GO Terms classification (by predefined parental GO terms such as GO Slim).
platform: web
description: CateGOrizer takes batch input of GO term IDs in a list format or unformatted plain text file, allows users to choose one of the available classifications such as GO_slim, GOA, EGAD, MGI_GO_slim, GO-ROOT, or a self-defined classification list, find its parental "branch" and performs an accumulative classification count, and returns the results in a sorted table of counts, percentages, and a pie chart (if it takes longer than standard "time out" period, it will email the user with a URL link to the results).
license: free_academic
pub_url: http://users.comcen.com.au/~journals/geneontologyabs2008.htm
go_data: term
go_data: rel
go_data: subset
go_data_other: GO_slim, GOA (slim), EGAD (slim), MGI_GO_slim
go_data_src: GO Terms such as "GO:000022"
update_frequency: quarterly
submission_date: 2010-06-03 08:15:04

id: classifi
name: Cluster Assignment for Biological Inference
name_abbr: CLASSIFI
url: http://pathcuric1.swmed.edu/pathdb/classifi.html
dev_id: pathcuric1_swmed
tool_type: statistical
platform: web
pub_pmid: 16670020
description: Cluster Assignment for Biological Inference is a data-mining tool that can be used to identify significant co-clustering of genes with similar functional properties (e.g. cellular response to DNA damage). Briefly, CLASSIFI uses the Gene Ontology gene annotation scheme to define the functional properties of all genes/probes in a microarray data set, and then applies a cumulative hypergeometric distribution analysis to determine if any statistically significant gene ontology co-clustering has occurred.
license: free_academic

id: clench
name: Cluster Enrichment
name_abbr: CLENCH
url: http://www.stanford.edu/~nigam/cgi-bin/dokuwiki/doku.php?id=clench
dev_id: bmir_stanford
tool_type: statistical
tool_type: slimmer
platform: linux
platform: win
pub_pmid: 14764555
description: CLuster ENriCHment allows <i class="spp">A. thaliana</i> researchers to perform automated retrieval of GO annotations from TAIR and calculate enrichment of GO terms in gene group with respect to a reference set. Before calculating enrichment, CLENCH allows mapping of the returned annotations to arbitrary coarse levels using GO slim term lists (which can be edited by the user) and a local installation of GO.
license: free_academic

id: db_for_dummies
name: Db for Dummies!
url: http://www.dbfordummies.com/go.asp
dev_id: custom_microsystems
tool_type: database
platform: win
description: Db for Dummies! is a small database that imports the Generic GO Slim. It allows data to be viewed in a tree.
license: free_academic

id: cluego
name: ClueGO
url: http://www.ici.upmc.fr/cluego
dev_id: ici_upmc_fr
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: win
pub_pmid: 19237447
description: ClueGO is a <a rel="external" href="http://www.cytoscape.org">Cytoscape</a> plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network. It can be used in combination with <a rel="external" href="http://www.pasteur.fr/recherche/unites/Biolsys/GOlorize/index.htm">GOlorize</a>. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easily extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be combined to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and <a rel="external" href="http://www.genome.jp/kegg/" title="Kyoto Encyclopedia of Genes and Genomes">KEGG</a>.
license: free_academic

id: cobra
name: COBrA
url: http://www.xspan.org/cobra
dev_id: xspan
tool_type: browser
platform: linux
platform: mac
platform: unix
platform: win
pub_pmid: 15513995
description: COBrA is a Java-based ontology editor for bio-ontologies that distinguishes itself from other editors by supporting the linking of concepts between two ontologies, and providing sophisticated analysis and verification functions. In addition to the Gene Ontology and Open Biology Ontologies formats, COBrA can import and export ontologies in the Semantic Web formats RDF, RDFS and OWL.
license: free_academic

id: david
name: Database for Annotation, Visualization and Integrated Discovery
name_acronym: DAVID
url: http://david.abcc.ncifcrf.gov
contactname: DAVID bioinformatics team
contactemail: huangdawei@mail.nih.gov
dev_id: niaid_nih
tool_type: term_enrichment
tool_type: text_mining
platform: web
pub_pmid: 12734009
pub_pmid: 19131956
description: Database for Annotation, Visualization and Integrated Discovery now provides a comprehensive set of functional annotation tools for investigators to understand biological meaning behind large list of genes, which are usually derived from high-throughtput experiments, such as micorarray and proteomic studies. By the year of 2010, DAVID tools have been cited in over 2,000 publications.
license: free_academic
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ref
go_data: taxon
go_data_src: obo
go_data_src: gaf
go_data_src: db
go_data_src: xml
go_data_src: other
update_frequency: no_fixed
submission_date: 2011-01-11 13:45:29

id: ctd
name: Comparative Toxicogenomics Database
name_acronym: CTD
url: http://ctd.mdibl.org
dev_id: mdibl
tool_type: browser
platform: web
pub_pmid: 12760826
pub_pmid: 14735110
pub_pmid: 16675512
pub_pmid: 16902965
description: The Comparative Toxicogenomics Database is a public database that enhances understanding about the effects of environmental chemicals on human health. Integrated GO data and a GO browser add functionality to CTD by allowing users to understand biological functions, processes and cellular locations that are the targets of chemical exposures.
license: free_academic

id: ease
name: EASE
url: http://david.abcc.ncifcrf.gov/content.jsp?file=/ease/ease1.htm&amp;type=1
dev_id: niaid_nih
tool_type: statistical
platform: win
pub_pmid: 12734009
description: EASE is useful for summarizing the predominant biological "theme" of a given gene list. Given a list of genes resulting from a microarray or other genome-scale experiment, EASE can rapidly calculate over-representation statistics for every possible Gene Ontology term with respect to all genes represented in the data set.
license: free_academic

id: dyngo
name: DynGO
url: http://gauss.dbb.georgetown.edu/liblab/dyngo.html
dev_id: gauss_dbb_georgetown
tool_type: browser
platform: linux
platform: unix
platform: win
pub_pmid: 16091147
description: DynGO is a client-server application that provides several advanced functionalities in addition to the standard browsing capability. DynGO allows users to conduct batch retrieval of GO annotations for a list of genes and gene products, and semantic retrieval of genes and gene products sharing similar GO annotations (which requires more disk and memory to handle the semantic retrieval). The result are shown in an association tree organized according to GO hierarchies and supported with many dynamic display options such as sorting tree nodes or changing orientation of the tree. For GO curators and frequent GO users, DynGO provides fast and convenient access to GO annotation data. DynGO is generally applicable to any data set where the records are annotated with GO terms, as illustrated by two examples.
license: free_academic

id: gopubmed
name: GoPubMed
url: http://gopubmed.org
dev_id: biotec_tu_dresden_de
tool_type: other_analysis
tool_type_other: literature curation and exploration
platform: web
pub_pmid: 15980585
description: GoPubMed is a web server which allows users to explore PubMed search results with the Gene Ontology. GoPubMed submits a user's keywords to PubMed, retrieves the abstracts, detects Gene Ontology terms in the abstracts, displays the subset of Gene Ontology relevant to the original query, and allows the user to browse through the ontology displaying associated papers and their GO annotation.
license: free_academic

id: gostat
name: GOstat
url: http://gostat.wehi.edu.au
dev_id: wehi
tool_type: statistical
platform: web
pub_pmid: 14962934
description: GOstat is an easy to use web tool to determine statistically significant over- or under-represented GO categories within lists of genes. Data files are updating monthly.
license: free_academic

id: goretriever
name: GORetriever
url: http://agbase.msstate.edu/cgi-bin/tools/goretriever_select.pl
contactemail: fmccarthy@cvm.msstate.edu
contactname: Fiona McCarthy
dev_id: agbase
tool_type: search
platform: web
pub_pmid: 17135208
description: GORetriever is used to find all of the GO annotations corresponding to a list of user-supplied protein identifiers. GORetriever produces a list of proteins and their annotations and a separate list of entries with no GO annotation.
license: free_academic
open_source: false
go_data: gp
go_data: ev_code
go_data: ref
go_data: qual
go_data: taxon
go_data_src: gaf
update_frequency: quarterly
submission_date: 2010-06-09 07:02:36

id: goslimviewer
name: GOSlimViewer
url: http://agbase.msstate.edu/cgi-bin/tools/goslimviewer_select.pl
contactemail: fmccarthy@cvm.msstate.edu
contactname: Fiona McCarthy
dev_id: agbase
tool_type: browser
tool_type: slimmer
platform: web
pub_pmid: 17135208
description: GOSlimViewer is used to summarize the GO function associated with a data set using prepared GO Slim sets. The input is a tab separated list of gene product IDs and GO IDs.
license: free_academic
open_source: false
go_data: term
go_data_src: other
update_frequency: quarterly
submission_date: 2010-06-09 07:10:20

id: gorilla
name: GOrilla
url: http://cbl-gorilla.cs.technion.ac.il/
contactemail: rnavon@gmail.com
contactname: Roy Navon
dev_id: agilent_labs_tel_aviv
dev_id: technion_laboratory_of_computational_biology
tool_type: statistical
tool_type: term_enrichment
tool_type: visualization
platform: web
pub_pmid: 19192299
description: GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. These are determined in a data driven manner. GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list. The tool supports several input formats: gene symbol, gene and protein RefSeq, Uniprot, Unigene and Ensembl. Supported organisms include: human, mouse, rat, yeast, zebrafish, D. melanogaster, C. elegans and A. thaliana. The input to GOrilla is either a ranked gene list or target and background sets. The graphical output shows the results in the context of the GO DAG.
license: free_academic
open_source: false
go_data: term
go_data: syn
go_data: rel
go_data: gp
go_data: qual
go_data: taxon
go_data_src: obo
go_data_src_other: NCBI
update_frequency: weekly
submission_date: 2010-08-17 06:20:27

id: gosurfer
name: GoSurfer
url: http://biosun1.harvard.edu/complab/gosurfer
dev_id: hsph
tool_type: statistical
platform: win
pub_url: http://biosun1.harvard.edu/complab/Zhong_S_GoSurfer2.pdf
description: GoSurfer uses Gene Ontology information in the analysis of gene sets obtained from genome-wide computations, microarray analysis or any other highly parallel method. It includes rigorous statistical testing, interactive graphics and automated updating of the annotation available for common gene identifiers (UniGene, LocusLink) or Affymetrix probe sets.
license: free_academic

id: gotcha
name: GOtcha
url: http://www.compbio.dundee.ac.uk/Software/GOtcha/gotcha.html
dev_id: compbio_dundee_ac_uk
tool_type: statistical
platform: web
pub_pmid: 15550167
description: GOtcha provides a prediction of a set of GO terms that can be assosciated with a given query sequence. Each term is scored independently and the scores calibrated against reference searches to give an accurate percentage likelihood of correctness. These results can be displayed graphically. <br>The tool is currently web-based; contact <a rel="external" href="http://www.compbio.dundee.ac.uk/About_Us/about_us.html#david">David Martin</a> for details of the standalone version.
license: free_academic

id: gotaxexplorer
name: GOTaxExplorer
url: http://www.gotaxexplorer.de/
contactemail: gotax@mpi-inf.mpg.de
contactname: GOTax Team
dev_id: mpi_inf_mpg_de
tool_type: database
tool_type: other_analysis
tool_type: search
tool_type: visualization
tool_type: functional_similarity
tool_type: semantic_similarity
tool_type_other: comparative genomics analysis
platform: web
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 17346342
description:  GOTaxExplorer presents a new approach to comparative genomics that integrates functional information and families with the taxonomic classification. It integrates UniProt, Gene Ontology, NCBI Taxonomy, Pfam and SMART in one database. GOTaxExplorer provides four different query types: selection of entity sets, comparison of sets of Pfam families, semantic comparison of sets of GO terms, functional comparison of sets of gene products.<br>This permits to select custom sets of GO terms, families or taxonomic groups. For example, it is possible to compare arbitrarily selected organisms or groups of organisms from the taxonomic tree on the basis of the functionality of their genes. Furthermore, it enables to determine the distribution of specific molecular functions or protein families in the taxonomy. The comparison of sets of GO terms allows to assess the semantic similarity of two different GO terms. The functional comparison of gene products makes it possible to identify functionally equivalent and functionally related gene products from two organisms on the basis of GO annotations and a semantic similarity measure for GO.
license: free_academic
go_data: term
go_data: rel
go_data: gp
go_data: ev_code
go_data: taxon
go_data_other: Pfam and SMART
go_data_src: go_ext_db
update_frequency: quarterly
submission_date: 2010-06-03 01:06:16

id: ep_go_browser
name: Expression Profiler
url: http://www.ebi.ac.uk/expressionprofiler/
dev_id: ebi
platform: web
tool_type: other_analysis
description: The EP:GO browser is built into EBI's <a rel="external" href="http://www.ebi.ac.uk/expressionprofiler/">Expression Profiler</a>, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.
license: free_academic

id: egan
name: Exploratory Gene Association Networks
name_acronym: EGAN
url: http://akt.ucsf.edu/EGAN
dev_id: cancer_ucsf
tool_type: statistical
platform: linux
platform: mac
platform: win
pub_pmid: 19933825
description: Exploratory Gene Association Networks is a software tool that allows a bench biologist to visualize and interpret the results of high-throughput exploratory assays in an interactive hypergraph of genes, relationships (protein-protein interactions, literature co-occurrence, etc.) and meta-data (annotation, signaling pathways, etc.). EGAN provides comprehensive, automated calculation of meta-data coincidence (over-representation, enrichment) for user- and assay-defined gene lists, and provides direct links to web resources and literature (NCBI Entrez Gene, PubMed, KEGG, Gene Ontology, <acronym title="International House of Pancakes">iHOP</acronym>, Google, etc.).
license: free_academic

id: fatigo
name: FatiGO
url: http://www.fatigo.org
dev_id: bioinfo_cipf_es
tool_type: statistical
platform: web
pub_pmid: 14990455
description: FatiGO assigns representative functional information (under-represented or over-represented Gene Ontology terms) to a given set of genes. Statistical significance is obtained using multiple-testing correction. FatiGO has been designed for functional annotation in the context of DNA microarray data analysis, and is linked to the <a rel="external" href="http://www.gepas.org">Gene Expression Pattern Analysis Suite</a>. FatiGO uses gene IDs from the major genomic and proteomic databases (GeneBank, UniProt, Unigene, Ensembl, etc.). FatiGO can also be used for functional annotation of any type of large-scale experiment.
license: free_academic

id: erminej
name: ermineJ
url: http://bioinformatics.ubc.ca/ermineJ
dev_id: ccbb
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: web
platform: win
pub_pmid: 16280084
description: ermineJ is a tool for the analysis of gene sets (user defined or those defined by GO terms) in expression data. The software is designed to be used by biologists with little or no informatics background. A command-line interface is available for users who wish to script the use of ermineJ. Several different methods for scoring gene sets are implemented, with a focus on methods that don't rely on simple "over-representation" measures.
license: free_academic

id: flash_gviewer
name: Flash GViewer
url: http://gmod.org/flashgviewer
dev_id: twigger_lab
tool_type: visualization
platform: web
description: Flash GViewer is a customizable Flash movie that can be easily inserted into a web page to display each chromosome in a genome along with the locations of individual features on the chromosomes. It is intended to provide an overview of the genomic locations of a specific set of features - eg. genes associated with a specific ontology term, etc., rather than as a way to view all features on the genome. The features can hyperlink out to a detail page to enable to GViewer to be used as a navigation tool. Genome maps for Rat, Mouse, Human and C. elegans are provided but other genome maps can be easily created. Annotation data can be provided as static text files or produced as XML via server scripts. <br>This tool is not GO-specific, but was built for the purpose of viewing GO annotation data.
license: free_academic

id: fiva
name: Functional Information Viewer and Analyzer
name_acronym: FIVA
url: http://bioinformatics.biol.rug.nl/standalone/fiva
dev_id: molgen_biol_rug_nl
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: win
pub_pmid: 17237043
description: Functional Information Viewer and Analyzer aids researchers in the prokaryotic community to quickly identify relevant biological processes following transcriptome analysis. Our software is able to assist in functional profiling of large sets of genes and generates a comprehensive overview of affected biological processes.
license: free_academic

id: funcassociate
name: FuncAssociate
url: http://llama.med.harvard.edu/cgi/func/funcassociate
dev_id: llama_med_harvard
tool_type: statistical
platform: web
pub_pmid: 14668247
description: FuncAssociate is a web-based tool that accepts as input a list of genes, and returns a list of GO attributes that are over- (or under-) represented among the genes in the input list. Only those over- (or under-) representations that are statistically significant, after correcting for multiple hypotheses testing, are reported. Currently 10 organisms are supported. In addition to the input list of genes, users may specify a) whether this list should be regarded as ordered or unordered; b) the universe of genes to be considered by FuncAssociate; c) whether to report over-, or under-represented attributes, or both; and d) the p-value cutoff.<br>A <a rel="external" href="http://llama.med.harvard.edu/cgi/func1/funcassociate">new version of FuncAssociate</a> (still at the beta stage!) is now available. This version supports a wider range of naming schemes for input genes, and uses more frequently updated GO associations. However, some features of the original version, such as sorting by LOD or the option to see the gene-attribute table, are not yet implemented.
license: free_academic

id: fsst
name: Functional Similarity Search Tool
name_acronym: FSST
url: http://www.gotaxexplorer.de/
contactemail: gotax@mpi-inf.mpg.de
contactname: GOTax Team
dev_id: mpi_inf_mpg_de
tool_type: other_analysis
tool_type_other: functional similarity search
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 17346342
description: The Functional Similarity Search Tool has been implemented for comparing user defined sets of annotated entities. FSST supports the computation of functional similarity scores based on an individual ontology and of combined scores. Its multi-threaded Java implementation takes advantage of symmetric multi-processing computers, decreasing runtime considerably.
license: free_academic
go_data: term
go_data: rel
go_data_src: go_ext_db
update_frequency: quarterly
submission_date: 2010-06-03 01:09:21

id: funcexpression
name: FuncExpression
url: http://www.barleybase.org/funcexpression.php
dev_id: iastate
tool_type: statistical
platform: web
description: FuncExpression is a web-based resource for functional interpretation of large scale genomics data. FuncExpression can be used for the functional comparison of plant, animal, and fungal gene name lists generated from genomics and proteomics experiments. Multiple gene lists can be classified, compared and visualized. FuncExpression supports two way-integration of plant gene functional information and the gene expression data, which allows for further cross-validation with plant microarray data from related experiments at BarleyBase.
license: free_academic

id: funspec
name: FunSpec
url: http://funspec.med.utoronto.ca
dev_id: utoronto
tool_type: statistical
platform: web
pub_pmid: 12431279
description: FunSpec is a web-based tool for statistical evaluation of groups of genes and proteins (e.g. co-regulated genes, protein complexes, genetic interactors) with respect to existing annotations, including GO terms.
license: free_academic

id: funcluster
name: FunCluster
url: http://corneliu.henegar.info/FunCluster.htm
dev_id: crc_jussieu_fr
dev_id: inserm
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: win
pub_pmid: 16046292
pub_pmid: 16506959
pub_pmid: 17007070
description: FunCluster is a genomic data analysis tool designed to perform a functional analysis of gene expression data obtained from cDNA microarray experiments. Besides automated functional annotation of gene expression data, FunCluster functional analysis allows to detect co-regulated biological processes (i.e. represented by annotating genomic themes) through a specifically designed co-clustering procedure involving biological annotations and gene expression data. FunCluster's functional analysis relies on Gene Ontology and KEGG annotations and is currently available for three organisms: <i class="spp">Homo sapiens</i>, <i class="spp">Mus musculus</i> and <i class="spp">Saccharomyces cerevisiae</i>.<br>FunCluster is provided as a standalone <a rel="external" href="http://www.r-project.org/" title="The R project for Statistical Computing">R</a> package, which can be run on any operating system for which an R environment implementation is available (Windows, Mac OS, various flavors of Linux and Unix). Download it from the <a rel="external" href="http://corneliu.henegar.info/FunCluster.htm">FunCluster website</a>, or from the <a rel="external" href="http://cran.r-project.org/mirrors.html" title="CRAN mirrors">worldwide mirrors of CRAN</a>. FunCluster is provided freely under the GNU General Public License 2.0.
license: free_academic

id: funnet
name: Functional Analysis of Transcriptional Networks
name_abbr: FunNet
url: http://www.funnet.info
dev_id: inserm
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: web
platform: win
pub_pmid: 18208606
description: Functional Analysis of Transcriptional Networks is designed as an integrative tool for analyzing gene co-expression networks built from microarray expression data. The analytical model implemented in this tool involves two abstraction layers: transcriptional (i.e. gene expression profiles) and functional (i.e. biological themes indicating the roles of the analyzed transcripts). A functional analysis technique, which relies on Gene Ontology and KEGG annotations, is applied to extract a list of relevant biological themes from microarray gene expression data. Afterwards multiple-instance representations are built to relate relevant biological themes to their annotated transcripts. An original non-linear dynamical model is used to quantify the contextual proximity of relevant genomic themes based on their patterns of propagation in the gene co-expression network (i.e. capturing the similarity of the expression profiles of the transcriptional instances of annotating themes). In the end an unsupervised multiple-instance spectral clustering procedure is used to explore the modular architecture of the co-expression network by grouping together biological themes demonstrating a significant relationship in the co-expression network. Functional and transcriptional representations of the co-expression network are provided, together with detailed information on the contextual centrality of related transcripts and genomic themes.<br>FunNet is provided both as a web-based tool and as a standalone <a rel="external" href="http://www.r-project.org/" title="The R project for Statistical Computing">R</a> package. The standalone R implementation can be run on any operating system for which an R environment implementation is available (Windows, Mac OS, various flavors of Linux and Unix) and can be downloaded from the <a rel="external" href="http://corneliu.henegar.info/FunNet.htm">FunNet website</a>, or from the <a rel="external" href="http://cran.r-project.org/mirrors.html" title="CRAN mirrors">worldwide mirrors of CRAN</a>. Both implementations of the FunNet tool are provided freely under the GNU General Public License 2.0.
license: free_academic

id: funsimmat
name: FunSimMat
url: http://www.funsimmat.de/
contactemail: funsimmat@mpi-inf.mpg.de
contactname: FunSimMat Team
dev_id: mpi_inf_mpg_de
tool_type: database
tool_type: functional_similarity
tool_type: semantic_similarity
tool_type_other: disease gene candidate prioritization
platform: web
pub_pmid: 17932054
pub_pmid: 19923227
description: FunSimMat is a comprehensive resource of semantic and functional similarity values. It allows ranking disease candidate proteins and searching for functional similarity values for proteins (extracted from UniProt), and protein families (Pfam, SMART). FunSimMat provides several different semantic and functional similarity measures for each protein pair using the Gene Ontology annotation from UniProtKB.
license: free_academic
go_data: term
go_data: gp
go_data: taxon
go_data_other: annotations to Pfam and SMART, OMIM
go_data_src_other: go_ext_db
update_frequency: quarterly
submission_date: 2010-06-03 01:01:20

id: fussimeg
name: Functional Semantic Similarity Measure between Gene Products
name_abbr: FuSSiMeG
url: http://xldb.fc.ul.pt/biotools/rebil/ssm/
contactemail: fcouto@di.fc.ul.pt
contactname: Francisco M Couto
dev_id: fc_ul
tool_type: other_analysis
tool_type: statistical
tool_type: term_enrichment
tool_type: semantic_similarity
platform: web
description: Functional Semantic Similarity Measure between Gene Products provides a functional similarity measure between two proteins using the semantic similarity between the GO terms annotated with the proteins.
open_source: false
pub_url: http://xldb.fc.ul.pt/xldb/publications/techreport03-29.pdf
go_data: term
go_data: xref
go_data: rel
go_data: gp
go_data: ev_code
go_data: ref
go_data_src: db
license: free_academic
update_frequency: quarterly
submission_date: 2010-06-04 04:48:16

id: g_profiler
name: g:Profiler
url: http://biit.cs.ut.ee/gprofiler
dev_id: biit_cs_ut_ee
contactname: BIIT support
contactemail: biit.support@ut.ee
tool_type: visualization
tool_type: statistical
tool_type: term_enrichment
tool_type: functional_similarity
tool_type: protein_interaction
tool_type: slimmer
tool_type: other_analysis
tool_type_other: Gene ID conversion, orthology mapping, coexpression similarity search, search by genomic locus, network enrichment analysis.
description_html: <p>g:Profiler is a public web server for characterising and manipulating gene lists from high-throughput genomic data. g:Profiler has a simple user-friendly web interface with powerful visualisation. g:Profiler currently supports 85 species, including mammals, fungi, plants, insects, etc, from the Ensembl and Ensembl Genomes databases. g:Profiler consists of the following tools:</p><ul><li>g:GOSt retrieves most significant Gene Ontology (GO) terms, KEGG and REACTOME pathways, and TRANSFAC motifs to a user-specified group of genes, proteins or microarray probes. g:GOSt also allows analysis of ranked or ordered lists of genes, visual browsing of GO graph structure, interactive visualisation of retrieved results, and many other features. Multiple testing corrections are applied to extract only statistically important results.</li><li>g:Convert allows conversion between gene or protein names, database IDs and microarray probes of more than 100 types. A mix of various IDs may be presented as input; output options include HTML, text and XLS spreadsheet.</li><li>g:Orth retrieves orthologs for a given set of genes, proteins or probes in a selected organism. Graphical representation also shows orthologs present in all g:Profiler organisms.</li><li>g:Sorter searches for similar expression profiles to a given gene, protein or probe in a large set of public microarray datasets from the Gene Expression Omnibus (GEO) database.</li><li>g:Cocoa provides a compact interface for comparing enrichments of multiple gene lists.</li></ul>
license: free_academic
open_source: false
platform: web
pub_pmid: 17478515
go_data: term
go_data: syn
go_data: rel
go_data: subset
go_data: gp
go_data: ev_code
go_data: taxon
go_data_src: obo
go_data_src_other: Most data (gene annotations, IDs, orthologs etc) retrieved from the Ensembl database.
update_frequency: quarterly
comments: Updates are processed according to Ensembl update schedule (normally every 2 months).
submission_date: 2011-01-26 17:00:16

id: g_sesame
name: G-SESAME
url: http://bioinformatics.clemson.edu/G-SESAME/
dev_id: bioinformatics_clemson
tool_type: functional_similarity
tool_type: semantic_similarity
platform: web
pub_pmid: 17344234
description: G-SESAME contains a set of tools. They include: tools for measuring the semantic similarity of GO terms; tools for measuring the functional similarity of genes; and tools for clustering genes based on their GO term annotation information.
license: free_academic

id: garban
name: GARBAN
url: http://www.garban.org/garban/home.php
dev_id: uni_navarra
tool_type: statistical
platform: web
pub_pmid: 14594726
description: GARBAN is a tool for analysis and rapid functional annotation of data arising from cDNA microarrays and proteomics techniques. GARBAN has been implemented with bioinformatic tools to rapidly compare, classify, and graphically represent multiple sets of data (genes/ESTs, or proteins), with the specific aim of facilitating the identification of molecular markers in pathological and pharmacological studies. GARBAN has links to the major genomic and proteomic databases (Ensembl, GeneBank, UniProt Knowledgebase, InterPro, etc.), and follows the criteria of the Gene Ontology Consortium (GO) for ontological classifications. Source may be shared: e-mail <span class="addr"><span class="id">garban</span>@<span class="place">ceit.es</span></span>.
license: free_academic

id: gene_class_expression
name: Gene Class Expression
url: http://gdm.fmrp.usp.br/cgi-bin/gc/upload/upload.pl
dev_id: gdm_fmrp_usp_br
tool_type: browser
platform: web
pub_pmid: 16755502
description: Gene Class Expression allows functional annotation of SAGE data using the Gene Ontology database. This tool performs searches in the GO database for each SAGE tag, making associations in the selected GO category for a level selected in the hierarchy. This system provides user-friendly data navigation and visualization for mapping SAGE data onto the gene ontology structure. This tool also provides graphical visualization of the percentage of SAGE tags in each GO category, along with confidence intervals and hypothesis testing.
license: free_academic

id: genecodis
name: GENECODIS
url: http://genecodis.dacya.ucm.es
dev_id: cnb_csic
dev_id: uc_madrid
tool_type: statistical
platform: web
pub_pmid: 17204154
description: GENECODIS is a web-based tool for the functional analysis of gene lists. It integrates different sources of information to search for annotations that frequently co-occur in a set of genes and rank them by their statistical significance. It allows the analysis of annotations from different databases such as GO, KEGG or SwissProt.
license: free_academic

id: geneinfoviz
name: GeneInfoViz
url: http://genenet2.uthsc.edu/geneinfoviz/search.php
dev_id: utmem
tool_type: browser
platform: web
pub_pmid: 15724283
description: GeneInfoViz is a web based tool for batch retrieval of gene function information, visualization of GO structure and construction of gene relation networks. It takes a input list of genes in the form of LocusLink ID, UniGeneID, gene symbol, or accession number and returns their functional genomic information. Based on the GO annotations of the given genes, GeneInfoViz allows users to visualize these genes in the DAG structure of GO, and construct a gene relation network at a selected level of the DAG.
license: free_academic

id: genemania
name: GeneMANIA
url: http://www.genemania.org
dev_id: genemania_team
contactname: GeneMANIA team
contactemail: genemania-discuss@googlegroups.com
tool_type: database
tool_type: software
tool_type: statistical
tool_type: term_enrichment
tool_type: other_analysis
tool_type_other: GeneMANIA is also a gene recommendation system, an interaction browser and GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest.
description: GeneMANIA helps you predict the function of your favourite genes and gene sets.<br>GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input.<br>If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets.<br>GeneMANIA also performs Gene Ontology term enrichment of the query list along with the returned gene list.<br>GeneMANIA is also accessible via a Cytoscape plugin, designed for power users.<br>GeneMANIA is actively developed at the University of Toronto, in the Donnelly Centre for Cellular and Biomolecular Research, in the labs of Gary Bader and Quaid Morris, with input from an independent scientific advisory board. GeneMANIA development was funded by Genome Canada, through the Ontario Genomics Institute (2007-OGI-TD-05).
license: free_academic
open_source: true
platform: web
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 20576703
pub_pmid: 20926419
go_data: term
go_data: rel
go_data: gp
go_data: ev_code
go_data: taxon
go_data_src: obo
go_data_src: gaf
go_data_src: db
update_frequency: quarterly
submission_date: 2011-01-13 10:48:01

id: genes2diseases
name: Genes2Diseases
url: http://coot.embl.de/g2d
dev_id: bork_embl_de
dev_id: embl
tool_type: database
platform: web
description: Genes2Diseases is a database of candidate genes for mapped inherited human diseases. The database is generated using an analysis of relations between phenotypic features and chemical objects, and from chemical objects to Gene Ontology protein function terms, based on the whole MEDLINE and RefSeq databases. Can be used to view all GO terms associated with a particular genetically inherited disease.
license: free_academic

id: genemerge
name: GeneMerge
url: http://genemerge.cbcb.umd.edu/
dev_id: castillo_lab
contactname: Dr. Cristian Castillo-Davis
contactemail: castill0@umd.edu
tool_type: statistical
tool_type: term_enrichment
tool_type: text_mining
tool_type: slimmer
tool_type_other: false discovery rate and Bonferroni correction
platform: linux
platform: mac
platform: unix
platform: web
platform: win
pub_pmid: 12724301
description: GeneMerge is a web-based and standalone application that returns a wide range of functional genomic data for a given set of study genes and provides rank scores for over-representation of particular functions or categories in the data. GeneMerge uses the hypergeometric test statistic which returns statistically correct results for samples of all sizes and is the #2 fastest GO tool available (Khatri and Draghici, 2005). GeneMerge can be used with any discrete, locus-based annotation data, including, literature references, genetic interactions, mutant phenotypes as well as traditional Gene Ontology queries.
license: free_academic
open_source: true
go_data: term
go_data: def
go_data: subset
go_data: gp
go_data: ref
go_data_other: GeneMerge uses a simple gene-association file format so it can be used with gene-association data beyond GO.
go_data_src: obo
go_data_src: gaf
update_frequency: quarterly
submission_date: 2011-01-14 19:26:56

id: generic_go_term_finder
name: Generic GO Term Finder
url: http://go.princeton.edu/cgi-bin/GOTermFinder
dev_id: genomics_princeton
contactname: Mark Schroeder
contactemail: gotools@genomics.princeton.edu
tool_type: visualization
tool_type: term_enrichment
description: The Generic GO Term Finder finds the significant GO terms shared among a list of genes from your organism of choice, displaying the results in a table and as a graph (showing the terms and their ancestry). The user may optionally provide background information or a custom gene association file or filter evidence codes. This tool is capable of batch processing multiple queries at once.
license: free_academic
open_source: false
platform: web
platform: win
platform: mac
platform: unix
platform: linux
go_data: term
go_data: rel
go_data: subset
go_data: gp
go_data: ev_code
go_data_other: ontology: regulation links
go_data_src: obo
go_data_src: gaf
update_frequency: daily
submission_date: 2011-02-19 03:30:04

id: generic_go_term_mapper
name: Generic GO Term Mapper
url: http://go.princeton.edu/cgi-bin/GOTermMapper
dev_id: genomics_princeton
contactname: Mark Schroeder
contactemail: gotools@genomics.princeton.edu
tool_type: term_enrichment
tool_type: slimmer
description: The Generic GO Term Mapper finds the GO terms shared among a list of genes from your organism of choice within a slim ontology, allowing them to be binned into broader categories. The user may optionally provide a custom gene association file or slim ontology, or a custom list of slim terms.
license: free_academic
open_source: false
platform: web
platform: win
platform: mac
platform: unix
platform: linux
go_data: term
go_data: rel
go_data: subset
go_data: gp
go_data: ev_code
go_data_src: obo
go_data_src: gaf
update_frequency: daily
submission_date: 2011-02-19 03:47:05

id: genetools
name: GeneTools
url: http://www.genetools.no
dev_id: ntnu_no
contactname: Vidar Beisvag
contactemail: vidar.beisvag@ntnu.no
tool_type: browser
tool_type: search
tool_type: visualization
tool_type: database
tool_type: statistical
tool_type: term_enrichment
platform: web
description_html: <p>GeneTools is a collection of web-based tools that brings together information from a broad range of resources, and provides this in a manner particularly useful for genome-wide analyses. Today, the two main tools connected to this database are the NMC Annotation Database V2.0 and eGOn V2.0 (explore Gene Ontology).</p><p>The NMC Annotation Database V2.0 provides information from UniGene, EntrezGene, SwissProt and Gene Ontology (GO). Major features are:</p><ul><li>Single search/Batch search, extraction of data for single or batches of genes.</li><li>Manage reporter lists: in folders and share selected lists with other users.</li><li>Manual GO Annotation: add your own Gene Ontology (GO) annotations to genes of interest.</li><li>Export: to Excel, text or XML format.</li></ul><p>eGOn V2.0 facilitates interpretation of GO annotation. GO terms are retrieved in batch modus from EntrezGene and the GO database and displayed in the GO directed acyclic hierarchical graph (DAG). Essential features of eGOn V2.0 are:</p><ul><li>Visualization: gene annotations are visualized in the GO DAG or as a table view. The granularity of the GO DAG can be edited freely by the user.</li><li>Filtering: GO annotations can be filtered on evidence codes.</li><li>Include user defined GO annotations: previously added to the Annotation database.</li><li>Statistical analysis: Several gene lists are analyzed simultaneously to compare the distribution of the annotated genes over the GO hierarchy.</li></ul><p>Statistical tests are implemented to allow the user to compute GO annotation dissimilarity within or between gene lists.</p><ul><li>Connection to Annotation database: Links to Annotation database gene and protein information are offered directly from the GO DAG or in exported data.</li><li>Export: GO DAG information, statistical results and gene and protein information can be exported in excel, text or XML format.</li></ul>
platform: web
pub_pmid: 17062145
go_data: term
go_data: def
go_data: syn
go_data: rel
go_data: gp
go_data: ev_code
go_data: ref
go_data_src: obo
go_data_src: db
update_frequency: no_fixed
license: free_academic
open_source: false
submission_date: 2011-01-18 10:49:22

id: gennav
name: GenNav
url: http://mor.nlm.nih.gov/perl/gennav.pl
dev_id: nlm_nih
tool_type: browser
platform: web
description: GenNav searches GO terms and annotated gene products, and provides a graphical display of a term's position in the GO DAG.
license: free_academic

id: gfinder
name: Genome Function INtegrated Discoverer
name_abbr: GFINDer
url: http://www.medinfopoli.polimi.it/GFINDer
dev_id: medinfopoli_polimi_it
dev_id: polimi_it
tool_type: statistical
platform: web
description: Genome Function INtegrated Discoverer is a multi-database system providing large-scale lists of user-classified sequence identifiers with genome-scale biological information and functional profiles biologically characterizing the different gene classes in the list. GFINDer automatically retrieves updated annotations of several functional categories from different sources, identifies the categories enriched in each class of a user-classified gene list, and calculates statistical significance values for each category. Moreover, GFINDer enables to functionally classify genes according to mined functional categories and to statistically analyse the obtained classifications, aiding in better interpreting microarray experiment results.
license: free_academic

id: go_db_perl
name: go-db-perl
url: http://search.cpan.org/~cmungall/go-db-perl
dev_id: goc
tool_type: software
tool_type: database
platform: linux
platform: mac
platform: unix
platform: win
description: go-db-perl extends the functionality of go-perl (on which it depends) with <a href="GO.database.shtml">GO Database</a> access functionality.<br>go-db-perl comes bundled with various scripts and a shell command line interface that can be used as standalone tools.<br>Installation is more involved than for go-perl; you will need a <a rel="external" href="http://dev.mysql.com">MySQL database</a> plus the requisite DBI and DBD Perl modules. Full installation instructions are included in the download.<br>go-db-perl is in use both to drive <a href="http://amigo.geneontology.org">AmiGO</a> and internally within <a rel="external" href="http://www.ensembl.org">Ensembl</a>.
update_frequency: na
license: free_academic
submission_date: 2010-10-10 10:10:10

id: go_slim_mapper
name: GO Slim Mapper
url: http://www.yeastgenome.org/cgi-bin/GO/goSlimMapper.pl
dev_id: sgd
tool_type: statistical
tool_type: slimmer
platform: web
description: The GO Slim Mapper (aka GO Term Mapper) maps the specific, granular GO terms used to annotate a list of budding yeast gene products to corresponding more general parent <a href="GO.slims.shtml" title="GO slim guide">GO slim</a> terms. Uses the SGD GO Slim sets.
license: free_academic

id: go_perl
name: go-perl
url: http://search.cpan.org/~cmungall/go-perl
dev_id: goc
tool_type: software
tool_type: slimmer
platform: linux
platform: mac
platform: unix
platform: win
description: go-perl is a set of Perl modules for parsing, manipulating and exporting ontologies and annotations. It includes parsers for the <a href="GO.format.obo-1_2.shtml">OBO</a> and <a href="GO.format.annotation.shtml">GO gene association</a> file formats. It has a graph-based object model with methods for graph traversal. For more details, see the documentation included with the modules.<br>go-perl comes bundled with <a rel="external" href="http://www.w3.org/Style/XSL/">XSL [Extensible Stylesheet Language] transforms</a> (which can also be used independently of Perl, provided you have files in <a href="GO.format.shtml#OBO-XML">OBO-XML format</a>), as well as scripts that can be used as standalone tools.<br>Installation should be simple, provided you have some experience with Perl and CPAN; see the INSTALL file for details.
update_frequency: na
license: free_academic
submission_date: 2010-10-10 10:10:10

id: goose
name: GO Online SQL Environment
name_acronym: GOOSE
url: http://www.berkeleybop.org/goose/
contactemail: gohelp@geneontology.org
contactname: GO Helpdesk
dev_id: goc
tool_type: database
platform: web
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 19033274
description: The GO Online SQL Environment provides a direct interface to the GO database, allowing users to run custom queries without having to install a copy of the GO database locally.
license: free_academic
open_source: true
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: subset
go_data: gp
go_data: ev_code
go_data: ref
go_data: qual
go_data: taxon
go_data_src: db
update_frequency: daily
submission_date: 2010-10-10 10:10:10

id: go_moose
name: go-moose
url: http://geneontology.svn.sourceforge.net/viewvc/geneontology/go-moose/
contactemail: gohelp@geneontology.org
contactname: GO Helpdesk
dev_id: berkeleybop
dev_id: goc
tool_type: other_analysis
tool_type: slimmer
tool_type: software
platform: linux
platform: mac
platform: unix
platform: win
description: go-moose is intended as a replacement for the aging go-perl and go-db-perl Perl libraries. It is written using the object oriented Moose libraries. It can be used for performing a number of analyses on GO data, including the remapping of GO annotations to a selected subset of GO terms.
license: free_academic
update_frequency: na
submission_date: 2011-01-01 10:10:10

id: goalie
name: Generalized Ontological Algorithmic Logical Invariants Extractor
name_acronym: GOALIE
url: http://bioinformatics.nyu.edu/Projects/GOALIE
dev_id: bioinformatics_nyu
tool_type: statistical
platform: win
platform: mac
platform: linux
description: Generalized Ontological Algorithmic Logical Invariants Extractor is a tool for the construction of time-course dependent enrichments. Requires an ODBC connection to an instance of the GO database.
license: free_academic

id: goblet
name: GOblet
url: http://goblet.molgen.mpg.de
dev_id: molgen_mpg
tool_type: browser
platform: web
pub_pmid: 15215401
description: The GOblet server performs analysis of sequences (cDNA, protein) with respect to GO terms. For similarity searches (BLAST), databases for various species are available, which were constructed using existing GO annotations. The server presents detailed descriptions of the matches and constructs a GO summary tree based on all GO terms of the respective hits.
license: free_academic

id: goarray
name: GOArray
url: http://goarray.med.yale.edu/GOArray/
dev_id: ycmi
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: win
description: GOArray is a Perl program which inputs a lists of genes annotated as "of interest" (GOI) or not, and determines if any associated GO terms have an overrepresentation of GOI. A permutation test is optionally used to assess confidence in the results. Output includes multiple visualizations and supplementary information and, for future reference, a summary of the statistical methods used.
license: free_academic

id: goanna
name: GOanna
url: http://www.agbase.msstate.edu/cgi-bin/tools/GOanna.cgi
contactemail: fmccarthy@cvm.msstate.edu
contactname: Fiona McCarthy
dev_id: agbase
tool_type: editor
tool_type: search
platform: web
pub_pmid: 17135208
description: GOanna is used to find annotations for proteins using a similarity search. The input can be a list of IDs or it can be a list of sequences in FASTA format. GOanna will retrieve the sequences if necessary and conduct the specified BLAST search against a user-specified database of GO annotated proteins. The resulting file contains GO annotations of the top BLAST hits. The sequence alignments are also provided so the user can use these to access the quality of the match.
license: free_academic
open_source: false
go_data: gp
go_data: ev_code
go_data: ref
go_data: qual
go_data: taxon
go_data_src: gaf
update_frequency: quarterly
submission_date: 2010-06-09 06:59:26

id: goannotator
name: GoAnnotator
url: http://xldb.fc.ul.pt/biotools/rebil/goa/
contactemail: fcouto@di.fc.ul.pt
contactname: Francisco M Couto
dev_id: fc_ul
tool_type: text_mining
platform: web
pub_pmid: 17181854
description: GOAnnotator is a tool for assisting the GO annotation of UniProt entries by linking the GO terms present in the uncurated annotations with evidence text automatically extracted from the documents linked to UniProt entries.
license: free_academic
open_source: false
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ev_code
go_data: ref
go_data_src: db
update_frequency: quarterly
submission_date: 2010-06-04 04:39:32

id: gochase
name: GOChase
url: http://www.snubi.org/software/GOChase
dev_id: snubi
tool_type: other_analysis
tool_type_other: historical views of GO
platform: web
pub_pmid: 15513987
description_html: <p><a rel="external" href="http://www.snubi.org/software/GOChase/">GOChase</a> is a set of web-based utilities to detect and correct the errors in GO-based annotations. </p><ul><li> GOChase-History resolves the whole modification history of GO IDs. </li><li> GOChase-Correct highlights merged GO IDs and redirects to the correct primary term into which the secondary ID was merged. For obsolete GO terms, the nearest non-discarded parent term is recommended by GOChase. This function may be used by GO browsers such as AmiGO and QuickGO to fix broken hyperlinks. </li><li> A whole database (such as LocusLink) as a flat file can be loaded into GOChase, reporting the annotation errors and GOChase corrections. </li><li> When one inputs a GO ID, GOChase will resolve all gene products annotated with the GO ID across all the major databases. </li></ul>
license: free_academic

id: gobu
name: Gene Ontology Browsing Utility
name_acronym: GOBU
url: http://gobu.iis.sinica.edu.tw
dev_id: iis_sinica_edu_tw
tool_type: visualization
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: web
platform: win
pub_url: http://www.iis.sinica.edu.tw/page/jise/2006/200601_02.html
description: Gene Ontology Browsing Utility is a Java-based software program for integrating biological annotation catalogs under an extendable architecture that uses the Gene Ontology and a user-defined hierarchy as two main atalogs. GOBU has the following features: (1) user-specified hierarchical data as input data, (2) user-defined data types for describing different annotations, and (3) an extendable software architecture for handling user-defined data types.
license: free_academic

id: goeast
name: Gene Ontology Enrichment Analysis Software Toolkit
name_acronym: GOEAST
url: http://omicslab.genetics.ac.cn/GOEAST
dev_id: genetics_ac_cn
tool_type: statistical
platform: web
pub_pmid: 18487275
description: Gene Ontology Enrichment Analysis Software Toolkit is a web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods.
license: free_academic

id: godist
name: GOdist
url: http://basalganglia.huji.ac.il/links.htm
dev_id: huji
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: win
pub_pmid: 15550480
description: GOdist is a Matlab program that analyzes Affymetrix microarray expression data implementing Kolmogorov-Smirnov (KS) continuous statistics approach. It also implements the discrete approach using Fisher exact test employing a two-tailed hypergeometric distribution. GOdist enables detection of both kinds of changes within specific GO terms represented on the array in relation to different populations: the global array population, the direct parents of the analyzed GO term and the global parent of it (e.g. biological process, molecular function or cellular component).
license: free_academic

id: goex
name: Gene Ontology Explorer
name_abbr: GOEx
url: http://pcarvalho.com/patternlab/goex.shtml
dev_id: cos_ufrj_br
dev_id: fields_scripps
tool_type: statistical
platform: win
pub_pmid: 19239707
description: Gene Ontology Explorer combines data from protein fold changes with GO over-representation statistics to help draw conclusions in proteomic experiments. It is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. A details description of these methods is provided in the publication.
license: free_academic

id: gofetcher
name: GOfetcher
url: http://mcbc.usm.edu/gofetcher/home.php
dev_id: mcbc_usm
dev_id: usm
tool_type: browser
platform: web
description: We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: 'Quick Search', 'Advanced Search', and 'Upload Files' for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format.
license: free_academic

id: gohypergall
name: GOHyperGAll
url: http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/R_BioCondManual.html#go
dev_id: ucr
tool_type: statistical
tool_type: slimmer
platform: linux
platform: mac
platform: unix
platform: win
description: To test a sample population of genes for overrepresentation of GO terms, the R/BioC function GOHyperGAll computes for all GO nodes a hypergeometric distribution test and returns the corresponding p-values. A subsequent filter function performs a GO Slim analysis using default or custom GO Slim categories. Basic knowledge about R and BioConductor is required for using this tool.
license: free_academic

id: gofish
name: GoFish
url: http://llama.med.harvard.edu/Software.html
dev_id: llama_med_harvard
tool_type: browser
platform: linux
platform: mac
platform: unix
platform: web
platform: win
pub_pmid: 12691998
description: The GoFish program, available as a Java applet online or to download, allows the user to construct arbitrary Boolean queries using GO attributes, and orders gene products according to the extent they satisfy such queries. GoFish also estimates, for each gene product, the probability that they satisfy the Boolean query.
license: free_academic

id: goffa
name: Gene Ontology For Functional Analysis
name_acronym: GOFFA
url: http://www.fda.gov/ScienceResearch/BioinformaticsTools/Arraytrack/default.htm
contactemail: hong.fang@fda.hhs.gov
contactname: Dr. Hong Fang
dev_id: fda_nctr
tool_type: browser
tool_type: database
tool_type: search
tool_type: statistical
tool_type: term_enrichment
tool_type: visualization
tool_type_other: integrated with and can be directly accessed from data stored in ArrayTrack
platform: web
pub_pmid: 17118145
description: Gene Ontology For Functional Analysis is accessed through ArrayTrack, and allows users to input a list of genes and find significant associated gene ontologies. Users can also browse for gene ontology terms in a hierarchical structure, search based on name, graphically view the most significant GO paths, and graphically view a simple tree structure showing the most significant GO terms (GO Tree Prune).
go_data: term
go_data: def
go_data: rel
go_data: gp
go_data: ev_code
go_data: taxon
go_data_src: go_ext_db
license: free_academic
update_frequency: no_fixed
submission_date: 2010-06-03 13:17:48

id: gonuts
name: Gene Ontology Normal Usage Tracking System
name_acronym: GONUTS
url: http://gowiki.tamu.edu
dev_id: ecoliwiki
contactname: Jim Hu
contactemail: jimhu@tamu.edu
tool_type: browser
tool_type: search
tool_type: editor
description: Gene Ontology Normal Usage Tracking System is a wiki-based system for using GO. GONUTS contains term pages where users can add or view notes elaborating on usage of GO terms. GONUTS also allows users to create and edit gene pages for any gene with a UniProt accession, and has tools to support annotation jamborees. GONUTS is the home of the CACAO (Community Assessment of Community Annotation with Ontologies) project to couple GO annotation to undergraduate education.
license: free_academic
open_source: true
platform: web
go_data: term
go_data: def
go_data: syn
go_data: rel
go_data: gp
go_data: ev_code
go_data: ref
go_data: qual
go_data: taxon
go_data_src: obo
go_data_src: gaf
go_data_src: db
go_data_src_other: UniProt flatfile dumps
update_frequency: no_fixed
submission_date: 2011-01-28 21:52:04

id: gomo
name: Gene Ontology for Motifs
name_abbr: GOMO
url: http://meme.nbcr.net
dev_id: imb_uq_edu_au
tool_type: editor
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: web
platform: win
pub_pmid: 18544606
pub_pmid: 20147307
description: Gene Ontology for Motifs is an alignment- and threshold-free comparative genomics approach for assigning functional roles to DNA regulatory motifs from DNA sequence. The algorithm detects associations between a user-specified DNA regulatory motif (expressed as a position weight matrix; <acronym title="position weight matrix">PWM</acronym>) and Gene Ontology terms. <br>The original method for predicting the roles of transcription factors (<acronym title="transcription factors">TF</acronym>s starts with a PWM motif describing the DNA-binding affinity of the <acronym title="transcription factors">TF</acronym>. GOMO uses the <acronym title="position weight matrix">PWM</acronym> to score the promoter region of each gene in the genome for its likelihood to be bound by the <acronym title="transcription factors">TF</acronym>. The resulting &lsquo;affinity&rsquo; scores are then used to test each term in the Gene Ontology for association with high-scoring genes. The algorithm was subsequently extended to leverage conserved signals using multiple, related species in a comparative approach, which greatly improves the resulting annotations.
license: free_academic

id: goprofiler
name: GOProfiler
url: http://agbase.msstate.edu/GOProfiler.html
dev_id: agbase
tool_type: browser
platform: web
description: GOProfiler provides a summary of the GO annotations available in AgBase. The user provides a species (taxon id) and GOProfiler displays the number of GO associations and the number of annotated proteins for that species. The results are listed by evidence code and a separate list of unannotated proteins is also provided.
license: free_academic

id: gotoolbox
name: GOToolBox
url: http://gin.univ-mrs.fr/GOToolBox
dev_id: ibdm_univ_mrs_fr
tool_type: statistical
tool_type: slimmer
platform: web
pub_pmid: 15575967
description: GOToolBox is a series of web-based programs allowing the identification of statistically over- or under-represented terms in a gene dataset relative to a reference gene set; the clustering of functionally related genes within a set; and the retrieval of genes sharing annotations with a query gene. GO annotations can also be constrained to a slim hierarchy or a given level of the ontology and terms can be filtered on evidence codes. Updated monthly with GO and gene association files.
license: free_academic

id: gotm
name: Gene Ontology Tree Machine
name_acronym: GOTM
url: http://bioinfo.vanderbilt.edu/gotm
dev_id: gst_ornl
dev_id: gst_tennessee
tool_type: statistical
platform: web
pub_pmid: 14975175
description: Gene Ontology Tree Machine is a web-based tool for the analysis and visualization of sets of interesting genes based on Gene Ontology hierarchies. This tool provides user friendly data navigation and visualization. It generates expandable tree for browsing the GO hierarchy, fixed tree as HTML output for archive and Bar charts at different annotation levels for publication. GOTM provides statistical analysis to indicate GO categories with relatively enriched gene numbers and suggest biological areas that warrant further study. Enriched GO categories can be visualized in Sub-trees or DAGs. Subset of genes can be retrieved by GO term or keyword searching. Detailed information for each gene can be retrieved directly from our a local database GeneKeyDB.
license: free_academic

id: graphweb
name: GraphWeb
url: http://biit.cs.ut.ee/graphweb/
dev_id: biit_cs_ut_ee
contactname: Laur Tooming
contactemail: laur_t@ut.ee
tool_type: visualization
tool_type: statistical
tool_type: term_enrichment
tool_type: protein_interaction
tool_type_other: Gene ID conversion; orthology mapping; network visualisation; graph clustering
description: GraphWeb allows the detection of modules from biological, heterogeneous and multi-species networks, and the interpretation of detected modules using Gene Ontology, cis-regulatory motifs and biological pathways.
license: free_academic
open_source: true
platform: web
pub_pmid: 18460544
go_data: term
go_data: syn
go_data: rel
go_data: gp
go_data: ev_code
go_data: qual
go_data_src_other: Ensembl
update_frequency: quarterly
comments: Data update frequency: In sync with Ensembl releases, usually every two months
submission_date: 2011-01-26 18:58:16

id: great
name: Genomic Regions Enrichment of Annotations Tool
name_acronym: GREAT
url: http://great.stanford.edu
contactemail: great-users@lists.stanford.edu
contactname: GREAT users mailing list
dev_id: bejerano_stanford
tool_type: term_enrichment
platform: web
pub_pmid: 20436461
description: We developed the Genomic Regions Enrichment of Annotations Tool to analyze the functional significance of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets.
license: free_academic
update_frequency: no_fixed
submission_date: 2010-05-01 10:20:30

id: high_throughput_gominer
name: High-Throughput GoMiner
url: http://discover.nci.nih.gov/gominer/GoCommandWebInterface.jsp
contactemail: barry@discover.nci.nih.gov
contactname: Barry Zeeberg
dev_id: discover_nci_nih
tool_type: term_enrichment
platform: web
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 12702209
pub_pmid: 15998470
description: We previously developed GoMiner, an application that organizes lists of 'interesting' genes (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology. The original version of GoMiner was oriented toward visualization and interpretation of the results from a single microarray (or other high-throughput experimental platform), using a graphical user interface. Although that version can be used to examine the results from a number of microarrays one at a time, that is a rather tedious task, and original GoMiner includes no apparatus for obtaining a global picture of results from an experiment that consists of multiple microarrays. We wanted to provide a computational resource that automates the analysis of multiple microarrays and then integrates the results across all of them in useful exportable output files and visualizations.<br>High-Throughput GoMiner, has those capabilities and a number of others: It (i) efficiently performs the computationally-intensive task of automated batch processing of an arbitrary number of microarrays, (ii) produces a human- or computer-readable report that rank-orders the multiple microarray results according to the number of significant GO categories, (iii) integrates the multiple microarray results by providing organized, global clustered image map visualizations of the relationships of significant GO categories, (iv) provides a fast form of 'false discovery rate' multiple comparisons calculation, and (v) provides annotations and visualizations for relating transcription factor binding sites to genes and GO categories.<br>High-Throughput GoMiner achieves the desired goal of providing a computational resource that automates the analysis of multiple microarrays and integrates results across all of the microarrays. High-Throughput GoMiner will be useful in a wide range of applications, including the study of time-courses, evaluation of multiple drug treatments, comparison of multiple gene knock-outs or knock-downs, and screening of large numbers of chemical derivatives generated from a promising lead compound.
license: free_academic
go_data: term
go_data: syn
go_data: xref
go_data: gp
go_data: ev_code
go_data: taxon
go_data_src: db
update_frequency: no_fixed
submission_date: 2010-06-03 05:49:33
comments: High-Throughput GoMiner generates integrative (categories versus experiments) clustered image maps (CIMs)that facilitate comparison of the results of multiple experiments. Additionally, there is an individual categories versus genes CIM for each experiment. That CIM relates categories based upon the genes they share in common.

id: interproscan
name: InterProScan
url: http://www.ebi.ac.uk/Tools/InterProScan
dev_id: ebi
tool_type: editor
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: web
pub_pmid: 15980438
pub_pmid: 17202162
description: Databases of protein domains and functional sites have become vital resources for the prediction of protein functions. During the last decade, several signature- recognition methods have evolved to address different sequence analysis problems, resulting in rather different and, for the most part, independent databases. Diagnostically, these resources have different areas of optimum application owing to the different strengths and weaknesses of their underlying analysis methods. Thus, for best results, search strategies should ideally combine all of them. InterProScan is a perl-based program which combines these different protein signature recognition methods into one resource.
license: free_academic

id: manatee
name: Manatee
url: http://manatee.sourceforge.net
dev_id: jcvi
tool_type: editor
tool_type: browser
platform: unix
platform: web
description: Manatee is a web-based gene evaluation and genome annotation tool; Manatee can store and view annotation for prokaryotic and eukaryotic genomes. The Manatee interface allows biologists to quickly identify genes and make high quality functional assignments, such as GO classifications, using search data, paralogous families, and annotation suggestions generated from automated analysis. Manatee can be downloaded and installed to run under the CGI area of a web server, such as Apache.
license: free_academic

id: lexgrid
name: LexGrid
url: http://www.lexgrid.org
dev_id: ebi
tool_type: software
platform: linux
platform: mac
platform: unix
platform: win
description: LexGrid is the foundation of the <a rel="external" href="http://www.ncbo.us">National Center for Biomedical Ontology</a> BioPortal interface and web-services. LexGrid can parse <a href="GO.format.obo-1_2.shtml">OBO format</a>, as well as other formats such as <a rel="external" href="http://www.w3.org/2004/OWL/">OWL</a>.
license: free_academic

id: l2l
name: L2L
url: http://depts.washington.edu/l2l
dev_id: biowww_washington
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: web
platform: win
pub_pmid: 16168088
description: L2L is a simple but powerful tool for discovering the hidden biological significance in microarray data. Through an easy-to-use web interface, L2L will mine a list of up- or down-regulated genes for Gene Ontology terms that are significantly enriched. L2L can also compare the list of genes to a database of hundreds of published microarray experiments, in order to identify common patterns of gene regulation. A downloadable command-line version can run customized and batch analyses.
license: free_academic

id: mappfinder
name: MAPPFinder
url: http://www.genmapp.org
dev_id: gladstone_institutes
tool_type: statistical
platform: win
pub_pmid: 12540299
description: MAPPFinder is an accessory program for <a rel="external" href="http://www.genmapp.org/">GenMAPP</a>. This program allows users to query any existing GenMAPP Expression Dataset Criterion against GO gene associations and GenMAPP MAPPs (microarray pathway profiles). The resulting analysis provides the user with results that can be viewed directly upon the Gene Ontology hierarchy and within GenMAPP, by selecting terms or MAPPs of interest.
license: free_academic

id: metagp
name: Meta Gene Profiler
name_abbr: MetaGP
url: http://metagp.ism.ac.jp
dev_id: ism_ac_jp
tool_type: statistical
platform: web
pub_url: http://metagp.ism.ac.jp/publication.html
description: Meta Gene Profiler is a web application tool for discovering differentially expressed gene sets (meta genes) from the gene set library registered in our database. Once user submits gene expression profiles which are categorized into subtypes of conditioned experiments, or a list of genes with the valid pvalues, MetaGP assigns the integrated p-value to each gene set by combining the statistical evidences of genes that are obtained from gene-level analysis of significance. The current version supports the nine Affymetrix GeneChip arrays for the three organisms (human, mouse and rat). The significances of GO terms are graphically mapped onto the directed acyclic graph (DAG). The navigation systems of GO hierarchy enable us to summarize the significance of interesting sub-graphs on the web browser.
license: free_academic

id: mgi_go_browser
name: MGI GO Browser
url: http://www.informatics.jax.org/searches/GO_form.shtml
dev_id: mgi
contactname: Joel Richardson
contactemail: jer@informatics.jax.org
tool_type: browser
tool_type: search
tool_type: visualization
platform: web
description: With the MGI GO Browser, you can search for a GO term and view all mouse genes annotated to the term or any subterms. You can also browse the ontologies to view relationships between terms, term definitions, as well as the number of mouse genes annotated to a given term and its subterms. The MGI GO browser directly accesses the GO data in the MGI database, which is updated nightly.
license: free_academic
open_source: false
go_data: term
go_data: def
go_data: syn
go_data_src: obo
update_frequency: no_fixed
submission_date: 2011-01-14 06:43:13

id: mev
name: MultiExperiment Viewer
name_abbr: MeV
url: http://www.tm4.org/mev.html
dev_id: tm4
tool_type: statistical
platform: linux
platform: mac
platform: win
pub_pmid: 16939790
description: MultiExperiment Viewer is a versatile microarray data analysis tool, incorporating sophisticated algorithms for clustering, visualization, classification, statistical analysis and biological theme discovery. Analyze gene expression or CGH microarray data and with MeV's many clustering, statistical analysis and graphical display tools. MeV generates informative and interrelated displays of expression and annotation data from single or multiple experiments.
license: free_academic

id: onex
name: Ontology Evolution Explorer
name_abbr: OnEx
url: http://www.izbi.de/onex
dev_id: izbi_de
tool_type: browser
platform: web
pub_pmid: 19678926
description: The Ontology Evolution Explorer is a web-based system for exploring ontology changes. It provides access to several versions of 16 well-known life science ontologies including the Gene Ontology. The system is based on a three-tier architecture including an ontology version repository, a middleware component and the OnEX web application. Interactive workflows allow a systematic and explorative change analysis of ontologies and their concepts as well as the semi-automatic migration of out-dated annotations to the current version of an ontology.
license: free_academic

id: obo_edit
name: OBO-Edit
url: http://oboedit.org
contactemail: gohelp@geneontology.org
contactname: GO Helpdesk
dev_id: goc
tool_type: browser
tool_type: editor
tool_type: search
tool_type: visualization
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 17545183
description: OBO-Edit is an open source, platform-independent application for viewing and editing any <a href="http://www.geneontology.org/GO.format.obo-1_2.shtml" title="The OBO file format in the File Format Guide">OBO format</a> ontologies. OBO-Edit is a graph-based tool; its emphasis on the overall graph structure of an ontology provides a friendly interface for biologists, and makes OBO-Edit excellent for the rapid generation of large ontologies focusing on relationships between relatively simple classes.</p><p>OBO-Edit uses the <a href="GO.downloads.shtml" title="Ontologies and Definitions from GO downloads">OBO format flat file</a>.
license: free_academic
open_source: true
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: subset
go_data_src: ont
update_frequency: na
submission_date: 2010-10-10 10:10:10

id: oe2go
name: Onto-Express To Go
name_abbr: OE2GO
url: http://vortex.cs.wayne.edu/projects.htm#OE2GO
contactemail: sorin@wayne.edu
contactname: Dr. Sorin Draghici
dev_id: vortex_cs_wayne
tool_type: browser
tool_type: other_analysis
tool_type: search
tool_type: statistical
tool_type: term_enrichment
tool_type: visualization
tool_type_other: custom level of abstraction, custom annotations
platform: web
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 17584796
description: Onto-Express is a web-based tool in the Onto-Tools suite that performs automated function profiling for a list of differentially expressed genes. However, Onto-Express does not support functional profiling for the organisms that do not have annotations in public domain, or use of custom (i.e. user-defined) ontologies. This limitation is also true for most of the other existing tools for functional profiling (10), which means that researchers working with uncommon organisms and/or new annotations or ontologies may be forced to construct such profiles manually. Onto-Express To Go is a new tool added to the Onto-Tools ensemble to address these issues. OE2GO is built on top of OE to leverage its existing functionality. In OE2GO, the users now have an option to use either the Onto-Tools database as a source of functional annotations or provide their own annotations in a separate file. Currently, OE2GO supports annotation file in the Gene Ontology format.
license: free_academic
open_source: false
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ref
go_data: taxon
go_data_src: obo
go_data_src: gaf
update_frequency: quarterly
submission_date: 2010-06-29 15:11:47

id: ontogate
name: OntoGate
url: http://functionalgenomics.de/ontogate
dev_id: mpi_inf_mpg_de
tool_type: statistical
platform: web
pub_pmid: 12824422
description: OntoGate provides access to <a rel="external" href="http://www.genome-matrix.org">GenomeMatrix</a> (GM) entries from Ontology terms and external datasets which have been associated with ontology terms, to find genes from different species in the GM, which have been mapped to the ontology terms. OntoGate includes a BLAST search of amino acid sequences corresponding to annotated genes.
license: free_academic

id: onto_perl
name: ONTO-PERL
url: http://search.cpan.org/dist/ONTO-PERL/
contactemail: erick.antezana@gmail.com
contactname: Erick Antezana
dev_id: ntnu
tool_type: software
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 18245124
description: ONTO-PERL is a collection of Perl modules to handle OBO-formatted ontologies (like the Gene Ontology). This code distribution gathers object-oriented modules (for dealing with ontology elements such as Term, Relationship and so forth), scripts (for typical tasks such as format conversions: obo2owl, owl2obo; besides, there are also many examples that can be easily adapted for specific applications), and a set of test files to ensure the suite's implementation quality.
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data_src: obo
license: free_academic
update_frequency: no_fixed
submission_date: 2010-08-09 05:24:19

id: onto_compare
name: Onto-Compare
url: http://vortex.cs.wayne.edu/projects.htm#Onto-Compare
contactemail: sorin@wayne.edu
contactname: Dr. Sorin Draghici
dev_id: vortex_cs_wayne
tool_type: browser
tool_type: database
tool_type: other_analysis
tool_type: search
tool_type: visualization
tool_type_other: compare commercially available microarrays based on GO
platform: web
pub_pmid: 15215428
pub_pmid: 12664686
description: Microarrays are at the center of a revolution in biotechnology, allowing researchers to screen tens of thousands of genes simultaneously. Typically, they have been used in exploratory research to help formulate hypotheses. In most cases, this phase is followed by a more focused, hypothesis driven stage in which certain specific biological processes and pathways are thought to be involved. Since a single biological process can still involve hundreds of genes, microarrays are still the preferred approach as proven by the availability of focused arrays from several manufacturers. Since focused arrays from different manufacturers use different sets of genes, each array will represent any given regulatory pathway to a different extent. We argue that a functional analysis of the arrays available should be the most important criterion used in the array selection. We developed Onto-Compare as a database that can provide this functionality, based on the GO nomenclature.
license: free_academic
open_source: false
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ref
go_data: taxon
go_data_src: obo
go_data_src: gaf
update_frequency: quarterly
submission_date: 2010-06-29 15:17:08

id: onto_design
name: Onto-Design
url: http://vortex.cs.wayne.edu/projects.htm#Onto-Design
contactemail: sorin@wayne.edu
contactname: Dr. Sorin Draghici
dev_id: vortex_cs_wayne
tool_type: browser
tool_type: database
tool_type: other_analysis
tool_type: search
tool_type: visualization
tool_type_other: design custom microarrays based on GO terms of interest
platform: web
pub_pmid: 15215428
description: Many Laboratories chose to design and print their own microarrays. At present, the choice of the genes to include on a certain microarray is a very laborious process requiring a high level of expertise. Onto-Design database is able to assist the designers of custom microarrays by providing the means to select genes based on their experiment.
license: free_academic
open_source: false
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ref
go_data: taxon
go_data_src: obo
go_data_src: gaf
update_frequency: quarterly
submission_date: 2010-06-29 15:20:16

id: onto_miner
name: Onto-Miner
name_abbr: OM
url: http://vortex.cs.wayne.edu/projects.htm#Onto-Miner
contactemail: sorin@wayne.edu
contactname: Dr. Sorin Draghici
dev_id: vortex_cs_wayne
tool_type: database
tool_type: other_analysis
tool_type: search
tool_type_other: scripted search of the Onto-Tools database for gene annotations
platform: web
pub_pmid: 15215428
pub_pmid: 17584796
description: Onto-Miner provide a single and convenient interface that allow the user to interrogate our databases regarding annotations of known genes. OM will return all known information about a given list of genes. Advantages or OM include the fact it allows queries with multiple genes and allows for scripting. This is unlike GenBank which uses a single gene navigation process.
license: free_academic
open_source: false
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ref
go_data: taxon
go_data_src: obo
go_data_src: gaf
update_frequency: quarterly
submission_date: 2010-06-29 15:26:20

id: onto_express
name: Onto-Express
name_abbr: OE
url: http://vortex.cs.wayne.edu/projects.htm#Onto-Express
contactemail: sorin@wayne.edu
contactname: Dr. Sorin Draghici
dev_id: vortex_cs_wayne
tool_type: browser
tool_type: database
tool_type: other_analysis
tool_type: search
tool_type: statistical
tool_type: term_enrichment
tool_type: visualization
tool_type_other: custom level of abstraction of the Gene Ontology
platform: web
pub_pmid: 11829497
pub_pmid: 12620386
pub_pmid: 15215428
description: The typical result of a microarray experiment is a list of tens or hundreds of genes found to be differentially regulated in the condition under study. Independently of the methods used to select these genes, the common task faced by any researcher is to translate these lists of genes into a better understanding of the biological phenomena involved. Currently, this is done through a tedious combination of searches through the literature and a number of public databases. We developed Onto-Express as a novel tool able to automatically translate such lists of differentially regulated genes into functional profiles characterizing the impact of the condition studied. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function and chromosome location. Statistical significance values are calculated for each category. We demonstrated the validity and the utility of this comprehensive global analysis of gene function by analyzing two breast cancer data sets from two separate laboratories. OE was able to identify correctly all biological processes postulated by the original authors, as well as discover novel relevant mechanisms (Draghici et.al, Genomics, 81(2), 2003). Other results obtained with Onto-Express can be found in Khatri et.al., Genomics. 79(2), 2002.
license: free_academic
open_source: false
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ref
go_data: taxon
go_data_src: obo
go_data_src: gaf
update_frequency: quarterly
submission_date: 2010-06-29 15:07:25

id: onto_translate
name: Onto-Translate
url: http://vortex.cs.wayne.edu/projects.htm#Onto-Translate
contactemail: sorin@wayne.edu
contactname: Dr. Sorin Draghici
dev_id: vortex_cs_wayne
tool_type: database
tool_type: other_analysis
tool_type_other: translate GO terms into other identifiers like GenBank accession number, Affymetrix probe IDs, Uniprot IDs, etc.
platform: web
pub_pmid: 15215428
description: In the annotation world, the same piece of information can be stored and viewed differently across different databases. For instance, more than one Affymetrix probe ID can refer to the same GenBank sequence (accession number) and more than one nucleotide sequence from GenBank can be grouped in a single UniGene cluster. The result of Onto-Express depends on whether the input list contains Affymetrix probe IDs, GenBank accession numbers or UniGene cluster IDs. The user has to be aware of relations between the different forms of the data in order to interpret correctly the results. Even if the user is aware of the relationships and knows how to convert them, most existing tools allow conversions of individual genes. Onto-Translate is a tool that allows the user to perform easily such translations.
license: free_academic
open_source: false
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ref
go_data: taxon
go_data_src: obo
go_data_src: gaf
update_frequency: quarterly
submission_date: 2010-06-29 15:23:51

id: ontology_lookup_service
name: Ontology Lookup Service
name_acronym: OLS
url: http://www.ebi.ac.uk/ontology-lookup/
dev_id: ebi
tool_type: browser
tool_type: search
platform: web
pub_pmid: 16507094
description: The Ontology Lookup Service was created to integrate publicly available biomedical ontologies into a single database. All modified ontologies are updated daily. A list of currently loaded ontologies is available online. The database can be queried to obtain information on a single term or to browse a complete ontology using AJAX. Auto-completion provides a user-friendly search mechanism. An AJAX-based ontology viewer is available to browse a complete ontology or subsets of it. A programmatic interface is available to query the webservice using SOAP. The service is described by a WSDL descriptor file available online. A sample Java client to connect to the webservice using SOAP is available for download from SourceForge. All OLS source code is publicly available under the open source Apache Licence. The OLS provides a user-friendly single entry point for publicly available ontologies in the Open Biomedical Ontology (OBO) format.
license: free_academic

id: org_geneontology_oboedit
name: org.geneontology.oboedit
url: http://www.oboedit.org
dev_id: goc
platform: linux
platform: mac
platform: unix
platform: win
tool_type: software
description: <a href="http://www.oboedit.org">OBO-Edit</a> is best known as a standalone application for editing ontologies. In fact, the UI components are cleanly separated from the data model and data adapters, so these can be reused in other applications. The oboedit foward-chaining reasoner can also be used independently (for example, for traversing ontology graphs).<br>org.geneontology.oboedit is used in tools such as the <a rel="external" href="http://www.ebi.ac.uk/ontology-lookup/">Ontology Lookup Service</a> and <a rel="external" href="http://www.phenote.org">Phenote</a>.<br>See the <a href="http://wiki.geneontology.org/index.php/OBO-Edit:_Getting_the_Source_Code">GO wiki</a> for instructions on downloading the source code.
license: free_academic
update_frequency: na
submission_date: 2010-10-10 10:10:10

id: owlapi
name: OWLAPI
url: http://owlapi.sourceforge.net
dev_id: cs_man_ac_uk
tool_type: software
platform: linux
platform: mac
platform: unix
platform: win
description: The OWLAPI is a java application programmer interface for <a rel="external" href="http://www.w3.org/2004/OWL/">OWL</a>-based ontologies. The latest version of the API contains an OBO-Format parser. The OWLAPI underpins ontology browsing and editing tools and platforms such as <a rel="external" href="http://www.mindswap.org/2004/SWOOP/">SWOOP</a> and Protege4.<br>Note that this API, or any other OWL-based API, can be used without an integrated OWL parser if you download a pre-converted OWL file generated from OBO. See <a rel="external" href="http://www.berkeleybop.org/ontologies/">OBO Ontologies List</a> for all OBO ontologies converted to OWL (we do not list the full complement of OWL-based APIs here, only those of direct relevance to GO).
license: free_academic

id: pandora
name: PANDORA
url: http://www.pandora.cs.huji.ac.il
dev_id: huji
tool_type: browser
platform: web
description: With PANDORA, you can search for any non-uniform sets of proteins and detect subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA supports GO annotations as well as additional keywords (from UniProt Knowledgebase, InterPro, ENZYME, SCOP etc). It is also integrated into the <a rel="external" href="http://www.protonet.cs.huji.ac.il">ProtoNet system</a>, thus allowing testing of thousands of automatically generated protein families. Note that PANDORA replaces the ProtoGO browser developed by the same group.
license: free_academic

id: pingo
name: PiNGO
url: http://www.psb.ugent.be/esb/PiNGO/
dev_id: psb_ugent_be
contactname: Steven Maere
contactemail: steven.maere@psb.vib-ugent.be
tool_type: search
tool_type: statistical
tool_type: term_enrichment
tool_type: functional_similarity
tool_type_other: functional prediction
description: PiNGO is a Java-based tool to easily find unknown genes in a network that are significantly associated with user-defined target Gene Ontology (GO) categories. PiNGO is implemented as a plugin for Cytoscape, a popular open source software platform for visualizing and integrating molecular interaction networks. PiNGO predicts the categorization of a gene based on the annotations of its neighbors, using the enrichment statistics of its sister tool BiNGO. Networks can either be selected from the Cytoscape interface or uploaded from file.
license: free_academic
open_source: true
platform: win
platform: mac
platform: unix
platform: linux
! publications: Smoot M, Ono K, Ideker T and Maere S (2010) PiNGO: a Cytoscape plugin to find candidate genes in biological networks. Bioinformatics (in press)
go_data: term
go_data: def
go_data: syn
go_data: rel
go_data: subset
go_data: gp
go_data: ev_code
go_data: qual
go_data: taxon
go_data_src: obo
go_data_src: gaf
go_data_src_other: NCBI, custom
update_frequency: no_fixed
submission_date: 2011-01-25 09:44:07

id: probe_explorer
name: Probe Explorer
url: http://probeexplorer.cicancer.org
dev_id: campus_usal_es
dev_id: cicancer
tool_type: statistical
platform: web
description: Probe Explorer is an open access web-based bioinformatics application designed to show the association between microarray oligonucleotide probes and transcripts in the genomic context, but flexible enough to serve as a simplified genome and transcriptome browser. Coordinates and sequences of the genomic entities (loci, exons, transcripts), including vector graphics outputs, are provided for fifteen metazoa organisms and two yeasts. Alignment tools are used to built the associations between Affymetrix microarrays probe sequences and the transcriptomes (for human, mouse, rat and yeasts). Search by keywords is available and user searches and alignments on the genomes can also be done using any DNA or protein sequence query.
license: free_academic

id: profcom
name: Profiling of Complex Functionality
name_abbr: ProfCom
url: http://webclu.bio.wzw.tum.de/profcom
dev_id: mips_helmholtz_muenchen_de
tool_type: statistical
platform: web
pub_pmid: 16959266
description: Profiling of Complex Functionality is a web-based tool for the functional interpretation of a gene list that was identified to be related by experiments. A trait which makes ProfCom a unique tool is an ability to profile enrichments of not only available Gene Ontology (GO) terms but also of <i>complex function</i>. A <i>complex function</i> is constructed as Boolean combination of available GO terms. The complex functions inferred by ProfCom are more specific in comparison to single terms and describe more accurately the functional role of genes.
license: free_academic

id: pubsearch
name: PubSearch
url: http://pubsearch.stanford.edu
dev_id: tair
tool_type: editor
tool_type_other: literature curation tool
platform: linux
platform: mac
platform: unix
platform: web
platform: win
description: PubSearch is a web-based literature curation tool, allowing curators to search and annotate genes to keywords from articles. It has a simple mySQL database backend and uses a set of Java Servlets and JSPs for querying, modifying, and adding gene, gene-annotation, and literature information. PubSearch can be downloaded from <a rel="external" href="http://gmod.org/pubsearch.shtml">GMOD</a>.
license: free_academic

id: proteinon
name: ProteInOn
url: http://xldb.di.fc.ul.pt/tools/proteinon/
contactemail: cpesquita@xldb.di.fc.ul.pt
contactname: Catia Pesquita
dev_id: fc_ul
tool_type: other_analysis
tool_type: statistical
tool_type: term_enrichment
tool_type: semantic_similarity
tool_type: protein_interaction
platform: web
description: ProteInOn calculates semantic similarity between GO terms or proteins annotated with GO terms. It also calculates term enrichment of protein sets, by applying a term representativity score, and gives additional information on protein interactions.
license: free_academic
open_source: false
pub_url: http://www.di.fc.ul.pt/tech-reports/07-6.pdf
go_data: term
go_data: rel
go_data: gp
go_data: ev_code
go_data_src: db
update_frequency: quarterly
submission_date: 2010-07-14 07:27:19

id: revigo
name: REViGO
url: http://revigo.irb.hr/
contactemail: fran.supek@irb.hr
contactname: Fran Supek
dev_id: rudjer_boskovic_institute
tool_type: statistical
tool_type: visualization
platform: web
pub_pmid: 20585573
description: REViGO summarizes lists of Gene Ontology terms by removing redundant terms and visualizing the remaining ones in scatterplots, interactive graphs, treemaps, or tag clouds
license: free_academic
open_source: false
go_data: term
go_data: def
go_data: syn
go_data: rel
go_data: gp
go_data: taxon
go_data_src: obo
go_data_src: gaf
go_data_src_other: GOA data from the EBI website
update_frequency: no_fixed
submission_date: 2010-06-02 10:39:10

id: quickgo
name: QuickGO
url: http://www.ebi.ac.uk/QuickGO/
contactemail: goa@ebi.ac.uk
contactname: Tony Sawford
dev_id: uniprotkb_goa
tool_type: browser
tool_type: database
tool_type: search
tool_type: visualization
tool_type: slimmer
platform: web
platform: win
platform: mac
platform: unix
platform: linux
pub_pmid: 19744993
pub_pmid: 20157483
description: QuickGO is a web-based tool that allows easy browsing of the Gene Ontology (GO) and all associated electronic and manual GO annotations provided by the GO Consortium annotation groups. QuickGO offers a range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation.
license: free_academic
open_source: true
go_data: term
go_data: def
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ev_code
go_data: ref
go_data: qual
go_data: taxon
go_data_other: Inter-ontology (Function-Process) links
go_data_src: obo
go_data_src: gaf
go_data_src: other
go_data_src_other: <a rel="external" href="http://www.proteinatlas.org/">Human Protein Atlas</a>, <a rel="external" href="http://www.ebi.ac.uk/intact">IntAct</a>, <a rel="external" href="http://www.dkfz.de/LIFEdb/">LifeDB</a>, <a rel="external" href="http://www.informatics.jax.org/">MGI</a>, <a rel="external" href="http://www.yeastgenome.org">SGD identifier mapping file</a>, <a rel="external" href="http://www.sanger.ac.uk/Projects/S_pombe/">S.pombe</a>
update_frequency: daily
submission_date: 2010-06-21 07:13:51

id: seqexpress
name: SeqExpress
url: http://www.seqexpress.com
dev_id: seqexpress
tool_type: statistical
platform: win
pub_pmid: 14988116
description: SeqExpress is a comprehensive analysis and visualisation package for gene expression experiments. GO is used to assign functional enrichment scores to clusters, using a combination of specially developed techniques and general statistical methods. These results can be explored using the in built ontology browsing tool or through the generated web pages. SeqExpress also supports numerous data transformation, projection, visualisation, file export/import, searching, integration (with R), and clustering options.
license: free_academic

id: serbgo
name: SerbGO
url: http://estbioinfo.stat.ub.es/apli/serbgo
dev_id: estbioinfo_stat_ub_es
dev_id: ir_vhebron_net
tool_type: statistical
platform: web
pub_pmid: 18480123
description: SerbGO is a web-based tool intended to assist researchers determine which microarray tools for gene expression analysis which make use of the GO ontologies are best suited to their projects. SerbGO is a bidirectional application. The user can ask for some features by checking on the Query Form to get the appropriate tools for their interests. The user can also compare tools to check which features are implemented in each one.
license: free_academic

id: source
name: SOURCE
url: http://source.stanford.edu
dev_id: smd_stanford
tool_type: statistical
platform: web
pub_pmid: 12519986
description: SOURCE compiles information from several publicly accessible databases, including UniGene, dbEST, UniProt Knowledgebase, GeneMap99, RHdb, GeneCards and LocusLink. GO terms associated with LocusLink entries appear in SOURCE.
license: free_academic

id: spotfire_gene_ontology_advantage_application
name: Spotfire Gene Ontology Advantage Application
url: http://spotfire.tibco.com
dev_id: spotfire_tibco
tool_type: statistical
platform: win
description: The Spotfire Gene Ontology Advantage Application integrates GO annotations with gene expression analysis in Spotfire DecisionSite for Functional Genomics. Researchers can select a subset of genes in DecisionSite visualizations and display their distribution in the Gene Ontology hierarchy. Similarly, selection of any process, function or cellular location in the Gene Ontology hierarchy automatically marks the corresponding genes in DecisionSite visualizations.
license: proprietary
inactive: true

id: stranger
name: StRAnGER
url: http://www.grissom.gr/stranger
dev_id: ibrb_nhrf
contactname: Panagiotis Moulos
contactemail: pmoulos@eie.gr
tool_type: visualization
tool_type: statistical
tool_type: term_enrichment
description: StRAnGER (Statistical  Ranking of ANotated Genomic Experimental Results) is a web application for the automated statistical analysis of annotated gene profiling experiments, exploiting controlled biological vocabularies, like the Gene Ontology or the KEGG pathways terms. Starting from annotated lists of differentially expressed genes StRAnGER repartitions and reorders the initial distribution of terms to define a new distribution of elements where each element pools terms holding the same enrichment score. The elements are then prioritized according to StRAnGER's algorithm and, by applying bootstrapping techniques, a corrected measure of the statistical significance of these elements is derived, enabling the selection of terms mapped to these elements, unambiguously associated with respective significant gene sets. Besides their high statistical score, another selection criterion for the terms is the number of their members, something that incurs a biological prioritization in line with a Systems Biology context.
open_source: false
platform: web
pub_doi: 10.3389/fnins.2011.00008
go_data: term
go_data: def
go_data: rel
go_data_src: obo
go_data_src: db
update_frequency: monthly
submission_date: 2011-01-26 22:38:21

id: tair_keyword_browser
name: TAIR Keyword Browser
url: http://www.arabidopsis.org/servlets/Search?action=new_search&amp;type=keyword
dev_id: tair
tool_type: browser
platform: web
description: TAIR Keyword Browser searches and browses for Gene Ontology, TAIR Anatomy, and TAIR Developmental stage terms, and allows you to view term details and relationships among terms. It includes links to genes, publications, microarray experiments and annotations associated with the term or any children terms.
license: free_academic

id: toppgene_suite
name: ToppGene Suite
url: http://toppgene.cchmc.org
dev_id: cchmc
contactname: Anil Jegga
contactemail: anil.jegga@cchmc.org
tool_type: database
tool_type: term_enrichment
tool_type: functional_similarity
tool_type: protein_interaction
tool_type: slimmer
tool_type: other_analysis
tool_type_other: disease gene ranking based on functional annotation similarity
description: ToppGene Suite is a one-stop portal for (i) gene list functional enrichment, (ii) candidate gene prioritization using either functional annotations or network analysis and (iii) identification and prioritization of novel disease candidate genes in the interactome. Functional annotation-based disease candidate gene prioritization uses a fuzzy-based similarity measure to compute the similarity between any two genes based on semantic annotations. The similarity scores from individual features are combined into an overall score using statistical meta-analysis. A P-value of each annotation of a test gene is derived by random sampling of the whole genome.
license: free_academic
open_source: false
platform: web
pub_pmid: 19465376
go_data: term
go_data: rel
go_data: gp
go_data_src: obo
go_data_src: gaf
update_frequency: no_fixed
submission_date: 2011-01-21 15:58:38

id: t_profiler
name: T-Profiler
url: http://www.t-profiler.org
dev_id: columbia
dev_id: uni_amsterdam
tool_type: statistical
platform: web
pub_pmid: 15980543
description: T-Profiler uses the t-test to score changes in the average activity of pre-defined groups of genes. The gene groups are defined based on Gene Ontology categorization, ChIP-chip experiments, upstream matches to a consensus transcription factor binding motif, and location on the same chromosome, respectively. A jack-knife procedure is used to make calculations more robust against outliers. T-profiler makes it possible to interpret microarray data in a way that is both intuitive and statistically rigorous, without the need to combine experiments or choose parameters.
license: free_academic

id: stem
name: Short Time-series Expression Miner
name_acronym: STEM
url: http://www.sb.cs.cmu.edu/stem
contactemail: jernst@cs.cmu.edu
contactname: Jason Ernst
dev_id: cmu
tool_type: statistical
tool_type: term_enrichment
platform: linux
platform: mac
platform: unix
platform: win
pub_pmid: 15961453
pub_pmid: 16597342
description: The Short Time-series Expression Miner is a Java program for clustering, comparing, and visualizing short time series gene expression data (eight time points or less). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database and supports GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category, identifying which temporal expression profiles were enriched for these genes.
license: free_academic
open_source: true
go_data: term
go_data: syn
go_data: xref
go_data: rel
go_data: gp
go_data: ev_code
go_data: qual
go_data: taxon
go_data_src: obo
go_data_src: gaf
go_data_src: other
update_frequency: no_fixed
submission_date: 2011-01-01 12:02:36

id: strap
name: STRAP
url: http://www.bumc.bu.edu/cardiovascularproteomics/strap/
dev_id: cpc_busm
contactname: Vivek Bhatia
contactemail: cpctools@gmail.com
tool_type: browser
tool_type: visualization
tool_type_other: Differential analysis of proteomics data sets
description: The Software Tool for Rapid Annotation of Proteins saves you time by automatically annotating a protein list with information that helps you meaningfully interpret your mass spectrometry data. STRAP takes protein lists as input, in the form of plain text files, protXML files (usually from the TPP), or Dat files from MASCOT search results. From this, STRAP generates protein annotation tables, and a variety of GO charts to aid individual and differential analysis of proteomics data, as shown below. It downloads information from mainly the Uniprot and EBI QuickGO databases. STRAP requires Windows XP or higher with at least version 3.5 of the Microsoft .NET Framework installed.
license: free_academic
open_source: true
platform: win
pub_doi: 10.1021/ac901335x
go_data: term
go_data: def
go_data: subset
go_data: gp
go_data_src: obo
go_data_src: xml
go_data_src: owl
go_data_src_other: UniProt
update_frequency: no_fixed
submission_date: 2011-02-09 20:43:04

id: txtgate
name: TXTGate
url: http://www.esat.kuleuven.ac.be/txtgate
dev_id: kuleuven_be
tool_type: text_mining
platform: web
pub_pmid: 15186494
description: TXTGate is a web-service that combines literature indices of selected public biological resources in a flexible text-mining system designed towards the analysis of groups of genes. By means of tailored vocabularies, selected textual fields and MedLine abstracts of LocusLink and SGD are indexed. Subclustering and links to external resources allow for an in-depth analysis of the resulting term profiles.
license: free_academic

id: tk_go
name: Tk-GO
url: https://github.com/manveru/tkgo
dev_id: illuminae
tool_type: browser
platform: linux
platform: mac
platform: unix
platform: win
description: Tk-GO is a <acronym title="Graphical user interface">GUI</acronym> wrapping the basic functions of the GO::AppHandle library from BDGP. GO terms are presented in an explorer-like browser, and behavior can be configured by altering Perl scripts. All available documentation is included in the download. Tk-GO uses the GO database (connects directly to the BDGP database by default) but is user-configurable.
license: free_academic

id: the_ontologizer
name: The Ontologizer
url: http://compbio.charite.de/index.php/ontologizer2.html
dev_id: charite_de
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: web
platform: win
pub_pmid: 17848398
pub_pmid: 18511468
description: The Ontologizer is a Java webstart application for GO term enrichment analysis that provides browsing and graph visualization capabilities. The Ontologizer allows users to analyze data with the standard Fisher exact test and also the parent-child method and topology methods.<br>The tool can be started directly from the web using Java webstart. For graph visualizations, users need to install the GraphViz library. The tool is freely available to all, and source code is available at SourceForge.
license: free_academic

id: thea
name: Tools for High-throughput Experiments Analysis
name_acronym: THEA
url: http://thea.unice.fr/index-en.html
dev_id: bioinfo_unice_fr
dev_id: unice_fr
tool_type: statistical
platform: linux
platform: mac
platform: unix
platform: win
pub_pmid: 15130932
description: Tools for High-throughput Experiments Analysis is an integrated information processing system dedicated to the analysis of post-genomic data. It allows automatic annotation of data issued from classification systems with selected biological information (including the Gene Ontology). Users can either manually search and browse through these annotations, or automatically generate meaningful generalizations according to statistical criteria (data mining).
license: free_academic

id: wego
name: Web Gene Ontology Annotation Plot
name_abbr: WEGO
url: http://wego.genomics.org.cn
dev_id: genomics_org_cn
tool_type: visualization
platform: web
description: Web Gene Ontology Annotation Plot is a simple but useful tool for plotting Gene Ontology (GO) annotation results. Different from other commercial software for chart creating, WEGO is designed to deal with the directed acyclic graph (DAG) structure of GO to facilitate histogram creation of GO annotation results. WEGO has been widely used in many important biological research projects, such as the rice genome project and the silkworm genome project. It has become one of the useful tools for downstream gene annotation analysis, especially when performing comparative genomics tasks.
license: free_academic

id: wandora
name: Wandora
url: http://www.wandora.org
dev_id: gripstudios
tool_type: browser
tool_type_other: knowledge management system
platform: linux
platform: mac
platform: unix
platform: win
description: Wandora is a general purpose knowledge extraction, management, and publishing environment based on Topic Maps (ISO 13250). Wandora supports OBO flat file v1.2 format and can convert OBO files, including the Gene Ontology, to a topic map and vice versa. Wandora is well suited to OBO visualizations and knowledge mashups combining OBO, RDF(S), and Topic Map resources for example.<br>Wandora requires Java v6.
license: free_academic

id: whatizit
name: Whatizit
url: http://www.ebi.ac.uk/webservices/whatizit
dev_id: rebholz_at_ebi
tool_type: other_analysis
tool_type_other: textual analysis
platform: web
description: Whatizit is a web application which highlights all kinds of "interesting" things in a document. One of its modules marks all GO terms as well as protein and gene names from UniProt and links them to their entries in GO and UniProt respectively.
license: free_academic