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 http://bioinfo.cau.edu.cn/agriGO/. 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:
This paper describes a new bioinformatic resource that will be of great use to any plant scientist carrying out genomic studies.
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.

AmiGO accesses the GO mySQL database; more information is available from the GO database guide. 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.
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.
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 A. thaliana 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 Cytoscape 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 GOlorize. 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 KEGG. 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&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.
The tool is currently web-based; contact David Martin 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.
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 Expression Profiler, 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, iHOP, 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 Gene Expression Pattern Analysis Suite. 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.
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.
A new version of FuncAssociate (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: Homo sapiens, Mus musculus and Saccharomyces cerevisiae.
FunCluster is provided as a standalone R 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 FunCluster website, or from the worldwide mirrors of CRAN. 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.
FunNet is provided both as a web-based tool and as a standalone R 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 FunNet website, or from the worldwide mirrors of CRAN. 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:

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:

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 garban@ceit.es. 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.
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.
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.
GeneMANIA also performs Gene Ontology term enrichment of the query list along with the returned gene list.
GeneMANIA is also accessible via a Cytoscape plugin, designed for power users.
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:

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).

The NMC Annotation Database V2.0 provides information from UniGene, EntrezGene, SwissProt and Gene Ontology (GO). Major features are:

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:

Statistical tests are implemented to allow the user to compute GO annotation dissimilarity within or between gene lists.

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 GO Database access functionality.
go-db-perl comes bundled with various scripts and a shell command line interface that can be used as standalone tools.
Installation is more involved than for go-perl; you will need a MySQL database plus the requisite DBI and DBD Perl modules. Full installation instructions are included in the download.
go-db-perl is in use both to drive AmiGO and internally within Ensembl. 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 GO slim 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 OBO and GO gene association file formats. It has a graph-based object model with methods for graph traversal. For more details, see the documentation included with the modules.
go-perl comes bundled with XSL [Extensible Stylesheet Language] transforms (which can also be used independently of Perl, provided you have files in OBO-XML format), as well as scripts that can be used as standalone tools.
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:

GOChase is a set of web-based utilities to detect and correct the errors in GO-based annotations.

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; PWM) and Gene Ontology terms.
The original method for predicting the roles of transcription factors (TFs starts with a PWM motif describing the DNA-binding affinity of the TF. GOMO uses the PWM to score the promoter region of each gene in the genome for its likelihood to be bound by the TF. The resulting ‘affinity’ 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.
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.
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 National Center for Biomedical Ontology BioPortal interface and web-services. LexGrid can parse OBO format, as well as other formats such as OWL. 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 GenMAPP. 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 OBO format 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.

OBO-Edit uses the OBO format flat file. 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 GenomeMatrix (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: OBO-Edit 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).
org.geneontology.oboedit is used in tools such as the Ontology Lookup Service and Phenote.
See the GO wiki 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 OWL-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 SWOOP and Protege4.
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 OBO Ontologies List 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 ProtoNet system, 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 complex function. A complex function 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 GMOD. 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: Human Protein Atlas, IntAct, LifeDB, MGI, SGD identifier mapping file, S.pombe 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&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 GUI 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.
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.
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