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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.
Software tool that uses a machine learning (ML) approach to classify text, based on the Gene Ontology. It relies on a k-Nearest Neighbours algorithm, a simple algorithm which assigns to a new text the categories that are the most prevalent among the k most similar instances contained in the knowledge base. The ML classifier operates in two steps and combines two components. First, a related article search engine retrieves instances (i.e. abstracts) in the knowledge base that are the most similar to the input text (its nearest neighbours); second, a score computer infers the functional profile from the k most similar instances.
Proper citation: GOCat (RRID:SCR_003608) Copy
http://mendel.stanford.edu/sidowlab/downloads/quest/
A Kernel Density Estimator-based package for analysis of massively parallel sequencing data from chromatin immunoprecipitation (ChIP-seq) experiments.
Proper citation: Quantitative Enrichment of Sequence Tags (RRID:SCR_004065) Copy
http://purl.bioontology.org/ontology/NIGO
Ontology that is a subset of GO directed for neurological and immunological systems. It was created by clipping those GO terms that are not associated to any gene in human, rat and mouse, and by clipping terms not found to be relevant to the neural and/or immune domains.
Proper citation: Neural-Immune Gene Ontology (RRID:SCR_004120) Copy
http://www.grissom.gr/stranger/
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. Platform: Online tool
Proper citation: StRAnGER (RRID:SCR_004247) Copy
http://dbserv2.informatik.uni-leipzig.de:8080/onex/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6,2023. Web-based application that integrates versions of 16 life science ontologies including the Gene Ontology, NCI Thesaurus and selected OBO ontologies with data leading back to 2002 in a common repository to explore ontology changes. It allows to study and apply the evolution of these integrated ontologies on three different levels. It provides global ontology evolution statistics and ontology-specific evolution trends for concepts and relationships and it allows the migration of annotations in case a new ontology version was released
Proper citation: OnEx - Ontology Evolution Explorer (RRID:SCR_000602) Copy
http://www.bioconductor.org/packages/release/bioc/html/categoryCompare.html
A software package for meta-analysis of high-throughput experiments using feature annotations. It calculates significant annotations (categories) in each of two (or more) feature (i.e. gene) lists, determines the overlap between the annotations, and returns graphical and tabular data about the significant annotations and which combinations of feature lists the annotations were found to be significant. Interactive exploration is facilitated through the use of RCytoscape (heavily suggested).
Proper citation: categoryCompare (RRID:SCR_001223) Copy
http://www.bioconductor.org/packages/release/bioc/html/globaltest.html
A software package that tests groups of covariates (or features) for association with a response variable. The package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.
Proper citation: globaltest (RRID:SCR_001256) Copy
A collaborative ontology for the definition of sequence features used in biological sequence annotation. SO was initially developed by the Gene Ontology Consortium. Contributors to SO include the GMOD community, model organism database groups such as WormBase, FlyBase, Mouse Genome Informatics group, and institutes such as the Sanger Institute and the EBI. Input to SO is welcomed from the sequence annotation community. The OBO revision is available here: http://sourceforge.net/p/song/svn/HEAD/tree/ SO includes different kinds of features which can be located on the sequence. Biological features are those which are defined by their disposition to be involved in a biological process. Biomaterial features are those which are intended for use in an experiment such as aptamer and PCR_product. There are also experimental features which are the result of an experiment. SO also provides a rich set of attributes to describe these features such as polycistronic and maternally imprinted. The Sequence Ontologies use the OBO flat file format specification version 1.2, developed by the Gene Ontology Consortium. The ontology is also available in OWL from Open Biomedical Ontologies. This is updated nightly and may be slightly out of sync with the current obo file. An OWL version of the ontology is also available. The resolvable URI for the current version of SO is http://purl.obolibrary.org/obo/so.owl.
Proper citation: SO (RRID:SCR_004374) Copy
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
System that classifies genes by their functions, using published scientific experimental evidence and evolutionary relationships to predict function even in absence of direct experimental evidence. Orthologs view is curated orthology relationships between genes for human, mouse, rat, fish, worm, and fly., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: PANTHER (RRID:SCR_004869) Copy
http://www.ebi.ac.uk/Rebholz-srv/ebimed/
A web application that combines Information Retrieval and Extraction from Medline. EBIMed finds Medline abstracts in the same way PubMed does. Then it goes a step beyond and analyses them to offer a complete overview on associations between UniProt protein/gene names, GO annotations, Drugs and Species. The results are shown in a table that displays all the associations and links to the sentences that support them and to the original abstracts. By selecting relevant sentences and highlighting the biomedical terminology EBIMed enhances your ability to acquire knowledge, relate facts, discover implications and, overall, have a good overview economizing the effort in reading.
Proper citation: EBIMed (RRID:SCR_005314) Copy
http://www.coremine.com/medical/#search
Service to access comprehensive information on diseases, drugs, treatments and medical biology. It is ideal for those seeking an overview of a complex subject while allowing the possibility to drill down to specific details. Search results are presented in a dashboard format comprized of panels containing various categories of information ranging from introductory sources to the latest scientific articles.
Proper citation: Coremine Medical (RRID:SCR_005323) Copy
http://cgap.nci.nih.gov/Genes/GOBrowser
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. Platform: Online tool
Proper citation: CGAP GO Browser (RRID:SCR_005676) Copy
http://vortex.cs.wayne.edu/projects.htm#Onto-Express
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 (OE) 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. Custom level of abstraction of the Gene Ontology. User account required. Platform: Online tool
Proper citation: Onto-Express (RRID:SCR_005670) Copy
Web-service providing access to database that brings together information from broad range of resources. Web application for functional annotation and statistical hypothesis testing. Provides tools for analysis of genomic and microarray data. Collection of tools include Bibliographic Information,Databases,Gene Annotation,Gene Regulation, Microarray,Proteins,Sequence Manipulation - Nucleic Acids,Sequence Manipulation - Protein, Systems Biology.
Proper citation: GeneTools (RRID:SCR_005663) Copy
http://search.cpan.org/~cmungall/go-perl/
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. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: go-perl (RRID:SCR_005730) Copy
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
http://manatee.sourceforge.net/
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. Platform: Online tool, Linux compatible, Solaris
Proper citation: Manatee (RRID:SCR_005685) Copy
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
http://basalganglia.huji.ac.il/links.htm
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). Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: GOdist (RRID:SCR_005770) Copy
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