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http://www.blast2go.com/b2ghome

An ALL in ONE tool for functional annotation of (novel) sequences and the analysis of annotation data. Blast2GO (B2G) 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. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Blast2GO (RRID:SCR_005828) Copy   

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http://www.gotaxexplorer.de/

The Functional Similarity Search Tool (FSST) 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. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FSST - Functional Similarity Search Tool (RRID:SCR_005819) Copy   

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http://www.bioconductor.org/

Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.

Proper citation: Bioconductor (RRID:SCR_006442) Copy   

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http://www.cdtdb.brain.riken.jp/CDT/Top.jsp

Transcriptomic information (spatiotemporal gene expression profile data) on the postnatal cerebellar development of mice (C57B/6J & ICR). It is a tool for mining cerebellar genes and gene expression, and provides a portal to relevant bioinformatics links. The mouse cerebellar circuit develops through a series of cellular and morphological events, including neuronal proliferation and migration, axonogenesis, dendritogenesis, and synaptogenesis, all within three weeks after birth, and each event is controlled by a specific gene group whose expression profile must be encoded in the genome. To elucidate the genetic basis of cerebellar circuit development, CDT-DB analyzes spatiotemporal gene expression by using in situ hybridization (ISH) for cellular resolution and by using fluorescence differential display and microarrays (GeneChip) for developmental time series resolution. The CDT-DB not only provides a cross-search function for large amounts of experimental data (ISH brain images, GeneChip graph, RT-PCR gel images), but also includes a portal function by which all registered genes have been provided with hyperlinks to websites of many relevant bioinformatics regarding gene ontology, genome, proteins, pathways, cell functions, and publications. Thus, the CDT-DB is a useful tool for mining potentially important genes based on characteristic expression profiles in particular cell types or during a particular time window in developing mouse brains.

Proper citation: Cerebellar Development Transcriptome Database (RRID:SCR_013096) Copy   

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http://www.phenogo.org

PhenoGO is a computed database designed for high throughput mining that provides phenotypic and experimental context - such as the cell type, disease, tissue, and organ - to existing annotations between gene products and Gene Ontology (GO) terms, as specified in the Gene Ontology Annotations (GOA) for multiple model organisms. Phenotypic and Experimental (P&E) contexts to identifiers are computationally mapped to general biological ontologies, including: the Cell Ontology (CO), phenotypes from the Unified Medical Language System (UMLS), species from Taxonomy of the National Center for Biotechnology Information (NCBI) taxonomy, and specialized ontologies such as Mammalian Phenotype Ontology (MP) and Mouse Anatomy (MA).

Proper citation: PhenoGO (RRID:SCR_013646) Copy   

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http://supfam.org/SUPERFAMILY/dcGO/

A database of domain-centric ontologies on functions, phenotypes, diseases and more. As a biomedical ontology resource, dcGO integrates functional, phenotypic, disease, and drug information. As a protein domain resource, it includes annotations to both the individual domains and supra-domains. Domain classifications and ontologies are organized in hierarchies, and dcGO includes the facility to browse the hierarchies: SCOP Hierarchy for browsing domains, GO Hierarchy for browsing GO terms, and BO Hierarchy for browsing other terms (mostly phenotypes). Users can mine and browse through resources.

Proper citation: dcGO (RRID:SCR_014392) Copy   

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http://bc02.iis.sinica.edu.tw/gobu/manual/index.html

Gene Ontology Browsing Utility (GOBU) (GOBU) is a Java-based software program for integrating biological annotation catalogs under an extendable software architecture. Users may interact with the Gene Ontology and user-defined hierarchy data of genes, and then use its plugins to (and not limited to) (1) browse the GO hierarchy with user defined data, (2) browse GO-oriented expression levels in the user data, (3) compute GO enrichment, and/or (4) customize data reporting. A set of classes and utility functions has been established so that a customized program can be made as a plugin or a command-line tool that programmically manipulate the Gene Ontology and specified user data. See the source code repository for examples. Reference Lin WD, Chen YC, Ho JM, Hsiao CD. GOBU: Toward an Integration Interface for Biological Objects. Journal of Information Science and Engineering. 2006 22(1):19-29. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Gene Ontology Browsing Utility (GOBU) (RRID:SCR_005662) Copy   

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http://owlapi.sourceforge.net/

The OWL API is a Java API and reference implementation for creating, manipulating and serializing OWL Ontologies. The latest version of the API is focused towards OWL 2. 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). The OWL API includes the following components: * An API for OWL 2 and an efficient in-memory reference implementation * RDF/XML parser and writer * OWL/XML parser and writer * OWL Functional Syntax parser and writer * Turtle parser and writer * KRSS parser * OBO Flat file format parser * Reasoner interfaces for working with reasoners such as FaCT++, HermiT, Pellet and Racer Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OWL API (RRID:SCR_005734) Copy   

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http://matrixdb.univ-lyon1.fr/

Freely available database focused on interactions established by extracellular proteins and polysaccharides, taking into account the multimeric nature of the extracellular proteins (e.g. collagens, laminins and thrombospondins are multimers). MatrixDB is an active member of the International Molecular Exchange (IMEx) consortium and has adopted the PSI-MI standards for annotating and exchanging interaction data. It includes interaction data extracted from the literature by manual curation, and offers access to relevant data involving extracellular proteins provided by the IMEx partner databases through the PSICQUIC webservice, as well as data from the Human Protein Reference Database. The database reports mammalian protein-protein and protein-carbohydrate interactions involving extracellular molecules. Interactions with lipids and cations are also reported. MatrixDB is focused on mammalian interactions, but aims to integrate interaction datasets of model organisms when available. MatrixDB provides direct links to databases recapitulating mutations in genes encoding extracellular proteins, to UniGene and to the Human Protein Atlas that shows expression and localization of proteins in a large variety of normal human tissues and cells. MatrixDB allows researchers to perform customized queries and to build tissue- and disease-specific interaction networks that can be visualized and analyzed with Cytoscape or Medusa. Statistics (2013): 2283 extracellular matrix interactions including 2095 protein-protein and 169 protein-glycosaminoglycan interactions.

Proper citation: MatrixDB (RRID:SCR_001727) Copy   

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http://datahub.io/dataset/kupkb

A collection of omics datasets (mRNA, proteins and miRNA) that have been extracted from PubMed and other related renal databases, all related to kidney physiology and pathology giving KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. Some microarray raw datasets have also been downloaded from the Gene Expression Omnibus and analyzed by the open-source software GeneArmada. The Semantic Web technologies, together with the background knowledge from the domain's ontologies, allows both rapid conversion and integration of this knowledge base. SPARQL endpoint http://sparql.kupkb.org/sparql The KUPKB Network Explorer will help you visualize the relationships among molecules stored in the KUPKB. A simple spreadsheet template is available for users to submit data to the KUPKB. It aims to capture a minimal amount of information about the experiment and the observations made.

Proper citation: Kidney and Urinary Pathway Knowledge Base (RRID:SCR_001746) Copy   

•   Source: SciCrunch Registry

https://rgd.mcw.edu/rgdweb/portal/home.jsp?p=4

An integrated resource for information on genes, QTLs and strains associated with diabetes. The portal provides easy acces to data related to both Type 1 and Type 2 Diabetes and Diabetes-related Obesity and Hypertension, as well as information on Diabetic Complications. View the results for all the included diabetes-related disease states or choose a disease category to get a pull-down list of diseases. A single click on a disease will provide a list of related genes, QTLs, and strains as well as a genome wide view of these via the GViewer tool. A link from GViewer to GBrowse shows the genes and QTLs within their genomic context. Additional pages for Phenotypes, Pathways and Biological Processes provide one-click access to data related to diabetes. Tools, Related Links and Rat Strain Models pages link to additional resources of interest to diabetes researchers.

Proper citation: Diabetes Disease Portal (RRID:SCR_001660) Copy   

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https://david.ncifcrf.gov/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.

Proper citation: DAVID (RRID:SCR_001881) Copy   

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http://mousecyc.jax.org/

A manually curated database of both known and predicted metabolic pathways for the laboratory mouse. It has been integrated with genetic and genomic data for the laboratory mouse available from the Mouse Genome Informatics database and with pathway data from other organisms, including human. The database records for 1,060 genes in Mouse Genome Informatics (MGI) are linked directly to 294 pathways with 1,790 compounds and 1,122 enzymatic reactions in MouseCyc. (Aug. 2013) BLAST and other tools are available. The initial focus for the development of MouseCyc is on metabolism and includes such cell level processes as biosynthesis, degradation, energy production, and detoxification. MouseCyc differs from existing pathway databases and software tools because of the extent to which the pathway information in MouseCyc is integrated with the wealth of biological knowledge for the laboratory mouse that is available from the Mouse Genome Informatics (MGI) database.

Proper citation: MouseCyc (RRID:SCR_001791) Copy   

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http://ahd.cbi.pku.edu.cn

Database providing a systematic and comprehensive view of morphological phenotypes regulated by plant hormones, as well as regulatory genes participating in numerous plant hormone responses. By integrating the data from mutant studies, transgenic analysis and gene ontology annotation, genes related to the stimulus of eight plant hormones were identified, including abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid and salicylic acid. Another pronounced characteristics of this database is that a phenotype ontology was developed to precisely describe all kinds of morphological processes regulated by plant hormones with standardized vocabularies. To increase the coverage of phytohormone related genes, the database has been updated from AHD to AHD2.0 adding and integrating several pronounced features: (1) added 291 newly published Arabidopsis hormone related genes as well as corrected information (e.g. the arguable ABA receptors) based on the recent 2-year literature; (2) integrated orthologues of sequenced plants in OrthoMCLDB into each gene in the database; (3) integrated predicted miRNA splicing site in each gene in the database; (4) provided genetic relationship of these phytohormone related genes mining from literature, which represents the first effort to construct a relatively comprehensive and complex network of hormone related genes as shown in the home page of our database; (5) In convenience to in-time bioinformatics analysis, they also provided links to a powerful online analysis platform Weblab that they have recently developed, which will allow users to readily perform various sequence analysis with these phytohormone related genes retrieved from AHD2.0; (6) provided links to other protein databases as well as more expression profiling information that would facilitate users for a more systematic analysis related to phytohormone research. Please help to improve the database with your contributions.

Proper citation: Arabidopsis Hormone Database (RRID:SCR_001792) Copy   

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http://www.megabionet.org/atpid/webfile/

Centralized platform to depict and integrate the information pertaining to protein-protein interaction networks, domain architecture, ortholog information and GO annotation in the Arabidopsis thaliana proteome. The Protein-protein interaction pairs are predicted by integrating several methods with the Naive Baysian Classifier. All other related information curated is manually extracted from published literature and other resources from some expert biologists. You are welcomed to upload your PPI or subcellular localization information or report data errors. Arabidopsis proteins is annotated with information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways.

Proper citation: Arabidopsis thaliana Protein Interactome Database (RRID:SCR_001896) Copy   

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http://www.candidagenome.org/

Database of genetic and molecular biological information about Candida albicans. Contains information about genes and proteins, descriptions and classifications of their biological roles, molecular functions, and subcellular localizations, gene, protein, and chromosome sequence information, tools for analysis and comparison of sequences and links to literature information. Each CGD gene or open reading frame has an individual Locus Page. Genetic loci that are not tied to DNA sequence also have Locus Pages. Provides Gene Ontology, GO, to all its users. Three ontologies that comprise GO (Molecular Function, Cellular Component, and Biological Process) are used by multiple databases to annotate gene products, so that this common vocabulary can be used to compare gene products across species. Development of ontologies is ongoing in order to incorporate new information. Data submissions are welcome.

Proper citation: Candida Genome Database (RRID:SCR_002036) Copy   

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https://scicrunch.org/resolver/SCR_002250

THIS RESOURCE IS NO LONGER IN SERVICE. Documented Jul 19, 2024. Metadatabase manually curated that provides web accessible tools related to genomics, transcriptomics, proteomics and metabolomics. Used as informative directory for multi-omic data analysis.

Proper citation: OMICtools (RRID:SCR_002250) Copy   

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http://genecruiser.broadinstitute.org/genecruiser3/

A web service and web application for the annotation of microarray data providing integrated access to genomic information freely available from public data sources.

Proper citation: GeneCruiser (RRID:SCR_003153) Copy   

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https://planttfdb.gao-lab.org/

Comprehensive plant transcription factor database. Interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis.PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors

Proper citation: PLANTTFDB (RRID:SCR_003362) Copy   

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https://bioportal.bioontology.org/ontologies/REX?p=classes&conceptid=http%3A%2F%2Fpurl.obolibrary.org%2Fobo%2FREX_0000000

An ontology of physico-chemical processes, i.e. physico-chemical changes occurring in course of time. It includes both microscopic processes (involving molecular entities or subatomic particles) and macroscopic processes. Some biochemical processes from Gene Ontology (GO Biological process) can be described as instances of REX.

Proper citation: Physico-Chemical Process (RRID:SCR_003530) Copy   

•   Source: SciCrunch Registry