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http://search.cpan.org/~cmungall/go-db-perl/

Software resource that 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. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: go-db-perl (RRID:SCR_005721) Copy   

•   Source: SciCrunch Registry

http://www.alliancegenome.org/

Organization that aims to develop and maintain sustainable genome information resources to promote understanding of the genetic and genomic basis of human biology, health, and disease. The Alliance is composed of FlyBase, Mouse Genome Database (MGD), the Gene Ontology Consortium (GOC), Saccharomyces Genome Database (SGD), Rat Genome Database (RGD), WormBase, and the Zebrafish Information Network (ZFIN).

Proper citation: Alliance of Genome Resources (RRID:SCR_015850) Copy   

•   Source: SciCrunch Registry

http://caintegrator-info.nci.nih.gov/rembrandt

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. REMBRANDT is a data repository containing diverse types of molecular research and clinical trials data related to brain cancers, including gliomas, along with a wide variety of web-based analysis tools that readily facilitate the understanding of critical correlations among the different data types. REMBRANDT aims to be the access portal for a national molecular, genetic, and clinical database of several thousand primary brain tumors that is fully open and accessible to all investigators (including intramural and extramural researchers), as well as the public at-large. The main focus is to molecularly characterize a large number of adult and pediatric primary brain tumors and to correlate those data with extensive retrospective and prospective clinical data. Specific data types hosted here are gene expression profiles, real time PCR assays, CGH and SNP array information, sequencing data, tissue array results and images, proteomic profiles, and patients'''' response to various treatments. Clinical trials'''' information and protocols are also accessible. The data can be downloaded as raw files containing all the information gathered through the primary experiments or can be mined using the informatics support provided. This comprehensive brain tumor data portal will allow for easy ad hoc querying across multiple domains, thus allowing physician-scientists to make the right decisions during patient treatments., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Repository of molecular brain neoplasia data (RRID:SCR_004704) Copy   

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http://genenet2.uthsc.edu/geneinfoviz/search.php

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. Platform: Online tool

Proper citation: GeneInfoViz (RRID:SCR_005680) Copy   

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http://www.cs.cmu.edu/~jernst/stem/

The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). 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 supporting 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 or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Short Time-series Expression Miner (STEM) (RRID:SCR_005016) Copy   

•   Source: SciCrunch Registry

http://integrativebiology.org/

Database for molecular interaction information integrated with various other bio-entity information, including pathways, diseases, gene ontology (GO) terms, species and molecular types. The information is obtained from several manually curated databases and automatic extraction from literature. There are protein-protein interaction, gene/protein regulation and protein-small molecule interaction information stored in the database. The interaction information is linked with relevant GO terms, pathway, disease and species names. Interactions are also linked to the PubMed IDs of the corresponding abstracts the interactions were obtained from. Manually curated molecular interaction information was obtained from BioGRID, IntAct, NCBI Gene, and STITCH database. Pathway related information was obtained from KEGG database, Pathway Interaction database and Reactome. Disease information was obtained from PharmGKB and KEGG database. Gene ontology terms and related information was obtained from Gene Ontology database and GOA database.

Proper citation: Integrated Molecular Interaction Database (RRID:SCR_003546) Copy   

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http://llama.mshri.on.ca/funcassociate/

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 37 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 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. Platform: Online tool

Proper citation: FuncAssociate: The Gene Set Functionator (RRID:SCR_005768) Copy   

•   Source: SciCrunch Registry

http://metagp.ism.ac.jp/

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Meta Gene Profiler (MetaGP) 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. Platform: Online tool

Proper citation: MetaGeneProfiler (RRID:SCR_005794) Copy   

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http://ccbb.jnu.ac.in/OntoVisT.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 07, 2013. Web based ontological visualization tool for interactive visualization of any ontological hierarchy for a specific node of interest, up to the chosen level of children and/or ancestor. It takes any ontology file in OBO format as input and generates output as DAG hierarchical graph for the chosen query. To enhance the navigation capabilities of complex networks, we have embedded several features such as search criteria, zoom in/out, center focus, nearest neighbor highlights and mouse hover events. The application has been tested on all 72 data sets available in OBO format through OBO foundry. The results for few of them can be accessed through OntoVisT-Gallery.

Proper citation: OntoVisT (RRID:SCR_005674) Copy   

•   Source: SciCrunch Registry

http://wego.genomics.org.cn/cgi-bin/wego/index.pl

Web Gene Ontology Annotation Plot (WEGO) 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. Platform: Online tool

Proper citation: WEGO - Web Gene Ontology Annotation Plot (RRID:SCR_005827) Copy   

•   Source: SciCrunch Registry

http://revigo.irb.hr/

Web server that summarizes lists of Gene Ontology terms by removing redundant terms and visualizing the remaining ones in scatterplots, interactive graphs, treemaps, or tag clouds. Platform: Online tool, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: REViGO (RRID:SCR_005825) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.clemson.edu/G-SESAME/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2,2025. 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. Platform: Online tool, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: G-SESAME - Gene Semantic Similarity Analysis and Measurement Tools (RRID:SCR_005816) Copy   

•   Source: SciCrunch Registry

http://malacards.org

An integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. The database contains 17,705 diseases, consolidated from 28 sources.

Proper citation: MalaCards (RRID:SCR_005817) Copy   

•   Source: SciCrunch Registry

http://web.cbio.uct.ac.za/ITGOM/

The Integrated Tool for IC-based GO Semantic Similarity Measures (IT-GOM) integrates the currently known GO semantic similarity measures into a single tool. It provides the information content (IC) of GO terms, semantic similarity between GO terms and GO-based protein functional similarity scores. The specificity of GO terms and the similarity of biological content between GO terms or proteins are transformed into numeric values for protein analyses at the functional level. The integration of the different measures enables users to choose the measure best suited to their application and to compare results between different semantic similarity measures. Platform: Online tool

Proper citation: IT-GOM: Integrated Tool for IC-based GO Semantic Similarity Measures (RRID:SCR_005815) Copy   

•   Source: SciCrunch Registry

http://www.jcvi.org/charprotdb/index.cgi/home

The Characterized Protein Database, CharProtDB, is designed and being developed as a resource of expertly curated, experimentally characterized proteins described in published literature. For each protein record in CharProtDB, storage of several data types is supported. It includes functional annotation (several instances of protein names and gene symbols) taxonomic classification, literature links, specific Gene Ontology (GO) terms and GO evidence codes, EC (Enzyme Commisssion) and TC (Transport Classification) numbers and protein sequence. Additionally, each protein record is associated with cross links to all public accessions in major protein databases as ��synonymous accessions��. Each of the above data types can be linked to as many literature references as possible. Every CharProtDB entry requires minimum data types to be furnished. They are protein name, GO terms and supporting reference(s) associated to GO evidence codes. Annotating using the GO system is of importance for several reasons; the GO system captures defined concepts (the GO terms) with unique ids, which can be attached to specific genes and the three controlled vocabularies of the GO allow for the capture of much more annotation information than is traditionally captured in protein common names, including, for example, not just the function of the protein, but its location as well. GO evidence codes implemented in CharProtDB directly correlate with the GO consortium definitions of experimental codes. CharProtDB tools link characterization data from multiple input streams through synonymous accessions or direct sequence identity. CharProtDB can represent multiple characterizations of the same protein, with proper attribution and links to database sources. Users can use a variety of search terms including protein name, gene symbol, EC number, organism name, accessions or any text to search the database. Following the search, a display page lists all the proteins that match the search term. Click on the protein name to view more detailed annotated information for each protein. Additionally, each protein record can be annotated.

Proper citation: CharProtDB: Characterized Protein Database (RRID:SCR_005872) Copy   

•   Source: SciCrunch Registry

http://www.utsouthwestern.edu/education/medical-school/departments/pathology/pathdb/classifi.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 10, 2012. Cluster Assignment for Biological Inference (CLASSIFI) 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. Platform: Online tool

Proper citation: CLASSIFI - Cluster Assignment for Biological Inference (RRID:SCR_005752) Copy   

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http://biit.cs.ut.ee/graphweb/

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. GraphWeb is a public web server for graph-based analysis of biological networks that: * analyses directed and undirected, weighted and unweighted heterogeneous networks of genes, proteins and microarray probesets for many eukaryotic genomes; * integrates multiple diverse datasets into global networks; * incorporates multispecies data using gene orthology mapping; * filters nodes and edges based on dataset support, edge weight and node annotation; * detects gene modules from networks using a collection of algorithms; * interprets discovered modules using Gene Ontology, pathways, and cis-regulatory motifs. Platform: Online tool

Proper citation: GraphWeb (RRID:SCR_005746) Copy   

•   Source: SciCrunch Registry

http://www.lasige.di.fc.ul.pt/webtools/proteinon/

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. The query compute protein semantic similarity returns the semantic similarity scores between all proteins entered, in matrix format. The option Measure allows users to choose one of several semantic similarity measures: Resnik, Lin, or Jiang & Conrath's measures with or without the DCA approach, plus the graph-based simUI and simGIC measures. These measures are listed by order of performance as evaluated with protein sequence similarity. The option GO type allows users to choose one of the aspects of GO: molecular function, biological process and cellular component. The option Ignore IEA limits the query to non-electronic annotations, excluding evidence types: IEA, NAS, ND, NR.

Proper citation: ProteInOn (RRID:SCR_005740) Copy   

•   Source: SciCrunch Registry

http://www.animalgenome.org/bioinfo/tools/catego/

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). This tool is comprised with a set of perl CGI programs coupled with a MySQL DBMS that stores the GO terms DAG data. Platform: Online tool

Proper citation: CateGOrizer (RRID:SCR_005737) Copy   

•   Source: SciCrunch Registry

http://www.berkeleybop.org/goose/

A web utility providing a direct interface to perform SQL queries directly on the GO database, allowing users to run custom queries without having to install a copy of the GO database locally. GOOSE includes many sample queries to aid novice users and allows results to be retrieved as a web page or as tab-delimited text. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GO Online SQL Environment (GOOSE) (RRID:SCR_006174) Copy   

•   Source: SciCrunch Registry