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http://go.princeton.edu/cgi-bin/GOTermMapper

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. The implementation of this Generic GO Term Mapper uses map2slim.pl script written by Chris Mungall at Berkeley Drosophila Genome Project, and some of the modules included in the GO-TermFinder distribution written by Gavin Sherlock and Shuai Weng at Stanford University, made publicly available through the GMOD project. GO Term Mapper serves a different function than the GO Term Finder. GO Term Mapper simply bins the submitted gene list to a static set of ancestor GO terms. In contrast, GO Term Finder finds the GO terms significantly enriched in a submitted list of genes. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Generic GO Term Mapper (RRID:SCR_005806) Copy   

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http://amp.pharm.mssm.edu/lib/chea.jsp

Data analysis service for gene-list enrichment analysis against a manual database. It allows users to input lists of mammalian gene symbols for which the program computes over-representation of transcription factor targets from the ChIP-X database. The database integrates interaction data from ChIP-chip, ChIP-seq, ChIP-PET and DamID studies and contains 189,933 interactions, manually extracted from 87 publications, describing the binding of 92 transcription factors to 31,932 target genes.

Proper citation: ChEA (RRID:SCR_005403) Copy   

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http://smd.stanford.edu/cgi-bin/source/sourceSearch

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. The mission of SOURCE is to provide a unique scientific resource that pools publicly available data commonly sought after for any clone, GenBank accession number, or gene. SOURCE is specifically designed to facilitate the analysis of large sets of data that biologists can now produce using genome-scale experimental approaches Platform: Online tool

Proper citation: SOURCE (RRID:SCR_005799) Copy   

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http://gdm.fmrp.usp.br/tools_bit.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. 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. Platform: Online tool

Proper citation: Gene Class Expression (RRID:SCR_005679) Copy   

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http://vortex.cs.wayne.edu/projects.htm#Onto-Compare

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. Compare commercially available microarrays based on GO. User account required. Platform: Online tool

Proper citation: Onto-Compare (RRID:SCR_005669) Copy   

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http://www.pathbase.net/

Database of histopathology photomicrographs and macroscopic images derived from mutant or genetically manipulated mice. The database currently holds more than 1000 images of lesions from mutant mice and their inbred backgrounds and further images are being added continuously. Images can be retrieved by searching for specific lesions or class of lesion, by genetic locus, or by a wide set of parameters shown on the Advanced Search Interface. Its two key aims are: * To provide a searchable database of histopathology images derived from experimental manipulation of the mouse genome or experiments conducted on genetically manipulated mice. * A reference / didactic resource covering all aspects of mouse pathology Lesions are described according to the Pathbase pathology ontology developed by the Pathbase European Consortium, and are available at the site or on the Gene Ontology Consortium site - OBO. As this is a community resource, they encourage everyone to upload their own images, contribute comments to images and send them their feedback. Please feel free to use any of the SOAP/WSDL web services. (under development)

Proper citation: Pathbase (RRID:SCR_006141) Copy   

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http://treebase.org/treebase-web/

Repository of phylogenetic information, specifically user-submitted phylogenetic trees and the data used to generate them. TreeBASE accepts all kinds of phylogenetic data (e.g., trees of species, trees of populations, trees of genes) representing all biotic taxa. Data in TreeBASE are exposed to the public if they are used in a publication that is in press or published in a peer-reviewed scientific journal, book, conference proceedings, or thesis. Data used in publications that are in preparation or in review can be submitted to TreeBASE but will not be available to the public until they have passed peer review.

Proper citation: TreeBASE (RRID:SCR_005688) Copy   

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http://www.brain-map.org

Seattle based independent, nonprofit medical research organization dedicated to accelerating the understanding of how human brain works. Provides free data and tools to researchers and educators and variety of unique online public resources for exploring the nervous system. Integrates gene expression data and neuroanatomy, along with data search and viewing tools, these resources are openly accessible via the Allen Brain Atlas data portal. Provides Allen Mouse Brain, Allen Spinal Cord Atlas, Allen Developing Mouse Brain Atlas, Allen Human Brain Atlas,Allen Mouse Brain Connectivity Atlas, Allen Cell Type Database, The Ivy Glioblastoma Atlas Project (Ivy GAP), The BrainSpan Atlas of the Developing Human Brain.

Proper citation: Allen Institute for Brain Science (RRID:SCR_006491) Copy   

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http://vmd.vbi.vt.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. Database covering a range of plant pathogenic oomycetes, fungi and bacteria primarily those under study at Virginia Bioinformatics Institute. The data comes from different sources and has genomes of 3 oomycetes pathogens: Phytophthora sojae, Phytophthora ramorum and Hyaloperonospora arabidopsidis. The genome sequences (95 MB for P.sojae and 65 MB for P.ramorum) were annotated with approximately 19,000 and approximately 16,000 gene models, respectively. Two different statistical methods were used to validate these gene models, Fickett''''s and a log-likelihood method. Functional annotation of the gene models is based on results from BlastX and InterProScan screens. From the InterProScan results, putative functions to 17,694 genes in P.sojae and 14,700 genes in P.ramorum could be assigned. An easy-to-use genome browser was created to view the genome sequence data, which opens to detailed annotation pages for each gene model. A community annotation interface is available for registered community members to add or edit annotations. There are approximately 1600 gene models for P.sojae and approximately 700 models for P.ramorum that have already been manually curated. A toolkit is provided as an additional resource for users to perform a variety of sequence analysis jobs.

Proper citation: VMD (RRID:SCR_004905) Copy   

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http://www.gene-talk.de

A web-based tool, knowledgebase and community for analysis and interpretation of human variant files. VCFs (Variant Call Formats) are preprocessed and annotated, you can filter them, access all databases and provide your expertise to the community by creating annotations.

Proper citation: GeneTalk (RRID:SCR_005231) Copy   

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https://www.ncbi.nlm.nih.gov/UniGene/help.cgi?item=DDD

Software tool for comparing EST profiles in order to identify genes with significantly different expression levels.

Proper citation: Digital Differential Display (DDD) (RRID:SCR_016638) Copy   

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https://www.jax.org/news-and-insights/2013/february/komp2-mice-phenotyping-and-availability

Knockout Mouse Phenotyping Project, JAX information about their contributions to KOMP2 project. Project to generate and phenotype single gene KO mouse strains from KOMP ES cell lines. Strains are phenotyped using protocols in pipeline designed by International Mouse Phenotyping Consortium. There are three NIH-funded phenotyping centers in United States: JAX, BaSH Consortium (Baylor College of Medicine, the Wellcome Trust Sanger Institute and MRC Harwell), and the DTCC Consortium (University of California at Davis, the Toronto Center for Phenogenomics, Children’s Hospital Oakland Research Institute (CHORI) and Charles River ).

Proper citation: KOMP2 (RRID:SCR_017528) Copy   

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https://github.com/AlexsLemonade/refinebio

Software tool to uniformly process and normalize large amounts of data. Harmonizes petabytes of publicly available biological data into ready-to-use datasets for cancer researchers and AI/ML scientists.

Proper citation: refine.bio (RRID:SCR_017471) Copy   

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https://github.com/lufuhao/ExonerateTransferAnnotation

Software tool as pipeline to make anntotations using cDNA and CDS sequences.

Proper citation: ExonerateTransferAnnotation (RRID:SCR_017557) Copy   

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http://bioinformatics.biol.rug.nl/standalone/fiva/

Functional Information Viewer and Analyzer (FIVA) 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. Currently, seven different modules containing functional information have been implemented: (i) gene regulatory interactions, (ii) cluster of orthologous groups (COG) of proteins, (iii) gene ontologies (GO), (iv) metabolic pathways (v) Swiss Prot keywords, (vi) InterPro domains - and (vii) generic functional categories. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FIVA - Functional Information Viewer and Analyzer (RRID:SCR_005776) Copy   

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http://www.betacell.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented on August 1, 2015. Consortium that aims to facilitate interdisciplinary collaborations to advance the understanding of pancreatic islet development and function, with the goal of developing innovative therapies to correct the loss of beta cell mass in diabetes, including cell reprogramming, regeneration and replacement. They are responsible for collaboratively generating the necessary reagents, mouse strains, antibodies, assays, protocols, technologies and validation assays that are beyond the scope of any single research effort. The scientific goals for the BCBC are to: * Use cues from pancreatic development to directly differentiate pancreatic beta cells and islets from stem / progenitor cells for use in cell-replacement therapies for diabetes, * Determine how to stimulate beta cell regeneration in the adult pancreas as a basis for improving beta cell mass in diabetic patients, * Determine how to reprogram progenitor / adult cells into pancreatic beta-cells both in-vitro and in-vivo as a mean for developing cell-replacement therapies for diabetes, and * Investigate the progression of human type-1 diabetes using patient-derived cells and tissues transplanted in humanized mouse models. Many of the BCBC investigator-initiated projects involve reagent-generating activities that will benefit the larger scientific community. The combination of programs and activities should accelerate the pace of major new discoveries and progress within the field of beta cell biology.

Proper citation: Beta Cell Biology Consortium (RRID:SCR_005136) Copy   

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https://neuinfo.org/mynif/search.php?list=cover&q=*

Service that partners with the community to expose and simultaneously drill down into individual databases and data sets and return relevant content. This type of content, part of the so called hidden Web, is typically not indexed by existing web search engines. Every record links back to the originating site. In order for NIF to directly query these independently maintained databases and datasets, database providers must register their database or dataset with the NIF Data Federation and specify permissions. Databases are concept mapped for ease of sharing and to allow better understanding of the results. Learn more about registering your resource, http://neuinfo.org/nif_components/disco/interoperation.shtm Search results are displayed under the Data Federation tab and are categorized by data type and nervous system level. In this way, users can easily step through the content of multiple resources, all from the same interface. Each federated resource individually displays their query results with links back to the relevant datasets within the host resource. This allows users to take advantage of additional views on the data and tools that are available through the host database. The NIF site provides tutorials for each resource, indicated by the Professor Icon professor icon showing users how to navigate the results page once directed there through the NIF. Additionally, query results may be exported as an Excel document. Note: NIF is not responsible for the availability or content of these external sites, nor does NIF endorse, warrant or guarantee the products, services or information described or offered at these external sites. Integrated Databases: Theses virtual databases created by NIF and other partners combine related data indexed from multiple databases and combine them into one view for easier browsing. * Integrated Animal View * Integrated Brain Gene Expression View * Integrated Disease View * Integrated Nervous System Connectivity View * Integrated Podcasts View * Integrated Software View * Integrated Video View * Integrated Jobs * Integrated Blogs For a listing of the Federated Databases see, http://neuinfo.org/mynif/databaseList.php or refer to the Resources Listed by NIF Data Federation table below.

Proper citation: NIF Data Federation (RRID:SCR_004834) Copy   

•   Source: SciCrunch Registry

http://www.ngfn.de/en/start.html

The program of medical genome research is a large-scale biomedical research project which extends the national genome research net (NGFN) and will be funded by the federal ministry of education and research (BMBF) from 2008-2013. Currently the program includes two fields: * Research ** NGFN-Plus: With the aim on combating diseases that are central to health policy, several hundred researchers are systematically investigating the complex molecular interactions of the human body. They are organized in 26 Integrated Genome Research Networks. * Application ** NGFN-Transfer: The rapid transfer of results from medical genome research into medical and industrial application is the aim of the scientists from research institutes and biomedical enterprises that cooperate in eight Innovation Alliances. AREAS OF DISEASE * Cardiovascular disease * Cancer * Neuronal diseases * Infections and Inflammations * Environmental factors

Proper citation: National Genome Research Network (RRID:SCR_006626) Copy   

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http://www.orpha.net/

European website providing information about orphan drugs and rare diseases. It contains content both for physicians and for patients. Reference portal for rare diseases and orphan drugs to help improve diagnosis, care and treatment of patients with rare diseases.

Proper citation: Orphanet (RRID:SCR_006628) Copy   

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http://www.seqexpress.com/

A comprehensive analysis and visualization software package for gene expression experiments that provides: a number of clustering and analysis techniques; integrated gene expression and analysis result visualizations, integration with the Gene Expression Omnibus; and an optional data sharing architecture. 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, visualization, file export/import, searching, integration (with R), and clustering options.

Proper citation: SeqExpress (RRID:SCR_007075) Copy   

•   Source: SciCrunch Registry