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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
https://bioconductor.org/packages/biomaRt/
Software package that integrates BioMart data resources with data analysis software in Bioconductor. Can annotate range of gene or gene product identifiers including Entrez Gene and Affymetrix probe identifiers with information such as gene symbol, chromosomal coordinates, Gene Ontology and OMIM annotation. Enables retrieval of genomic sequences and single nucleotide polymorphism information, which can be used in data analysis.
Proper citation: biomaRt (RRID:SCR_019214) Copy
http://snf-515788.vm.okeanos.grnet.gr/
Web tool for integrating human and mouse microRNAs in pathways.Pathway analysis web-server, providing statistics, while being able to accommodate advanced pipelines. Web server for assessment of miRNA regulatory roles and identification of controlled pathways. Supports all analyses for KEGG molecular pathways and Gene Ontology (GO) in seven species (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Caenorhabditis elegans, Gallus gallus and Danio rerio).DIANA miRPath v.2.0 includes investigating combinatorial effect of microRNAs in pathways.DIANA-miRPath v3.0 includes deciphering microRNA function with experimental support., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: DIANA-mirPath (RRID:SCR_017354) Copy
http://www.informatics.jax.org/function.shtml
MGI GO project provides functional annotations for mouse gene products using Gene Ontology. Functional annotation using Gene Ontology (GO).
Proper citation: Functional Annotation (RRID:SCR_017519) Copy
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
http://www.bumc.bu.edu/cardiovascularproteomics/cpctools/strap/
Software program that automatically annotates a protein list with information that helps in the meaningful interpretation of data from mass spectrometry and other techniques. It 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, it generates protein annotation tables, and a variety of GO charts to aid individual and differential analysis of proteomics data. 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. Platform: Windows compatible
Proper citation: STRAP (RRID:SCR_005675) Copy
http://www.cs.ualberta.ca/~bioinfo/PA/GOSUB/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 30, 2015. Refer to Proteome Analyst 3.0. Subcellular Localization and GO General Molecular Function predictions for many model organism proteomes using Protein Analyst, with a very high coverage rate. When users blast their proteins against the database of results, they will not only be shown blast homologs from the model organisms, but also the Subcellular Localization and GO General Molecular Function predictions as well.
Proper citation: Proteome Analyst PA-GOSUB (RRID:SCR_008234) Copy
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
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
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
http://functionalgenomics.de/ontogate/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 13, 2012. 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. Platform: Online tool
Proper citation: OntoGate (RRID:SCR_005795) Copy
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
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
Network Ontology Analysis (NOA) (abbreviated to NOA) is a freely available collection of Gene Ontology tools aiming to analyze functions of gene network instead of gene list. Network rewiring facilitates the function changes between conditions even with the same gene list. Therefore, it is necessary to annotate the specific function of networks by considering the fundamental roles of interactions from the viewpoint of systems biology. NOA is such a novel functional enrichment analysis method capable to handle both dynamic and static networks. The application of NOA in biological networks shows that NOA can not only capture changing functions in rewiring networks but also find more relevant and specific functions in traditional static networks. Platform: Online tool
Proper citation: Network Ontology Analysis (RRID:SCR_005667) Copy
http://snps-and-go.biocomp.unibo.it/snps-and-go/
A server for the prediction of single point protein mutations likely to be involved in the insurgence of diseases in humans.
Proper citation: SNPsandGO (RRID:SCR_005788) Copy
OBO-Edit is an open source, platform-independent application written in Java 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. 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). OBO-Edit uses the OBO format flat file. See the GO wiki, http://wiki.geneontology.org/index.php/OBO-Edit:_Getting_the_Source_Code, for instructions on downloading the source code. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: OBO-Edit (RRID:SCR_005668) Copy
A curated repository of more than 206000 regulatory associations between transcription factors (TF) and target genes in Saccharomyces cerevisiae, based on more than 1300 bibliographic references. It also includes the description of 326 specific DNA binding sites shared among 113 characterized TFs. Further information about each Yeast gene has been extracted from the Saccharomyces Genome Database (SGD). For each gene the associated Gene Ontology (GO) terms and their hierarchy in GO was obtained from the GO consortium. Currently, YEASTRACT maintains a total of 7130 terms from GO. The nucleotide sequences of the promoter and coding regions for Yeast genes were obtained from Regulatory Sequence Analysis Tools (RSAT). All the information in YEASTRACT is updated regularly to match the latest data from SGD, GO consortium, RSA Tools and recent literature on yeast regulatory networks. YEASTRACT includes DISCOVERER, a set of tools that can be used to identify complex motifs found to be over-represented in the promoter regions of co-regulated genes. DISCOVERER is based on the MUSA algorithm. These algorithms take as input a list of genes and identify over-represented motifs, which can then be compared with transcription factor binding sites described in the YEASTRACT database.
Proper citation: Yeast Search for Transcriptional Regulators And Consensus Tracking (RRID:SCR_006076) Copy
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
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
http://tomcat.esat.kuleuven.be/txtgate/
TXTGate is a literature index database and is part of an experimental platform to evaluate (combinations of) information extraction and indexing from a variety of biological annotation databases. It is designed towards the summarization and analysis of groups of genes based on text. 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. You need to be registered in order to use the TXTGate application. Platform: Online tool
Proper citation: TXTGate (RRID:SCR_005812) Copy
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
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