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http://genemania.org/

Data analysis service to predict the function of your favorite genes and gene sets. Indexing 1,421 association networks containing 266,984,699 interactions mapped to 155,238 genes from 7 organisms. GeneMANIA interaction networks are available for download in plain text format. GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets. GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest. GeneMANIA is also a gene recommendation system. GeneMANIA is also accessible via a Cytoscape plugin, designed for power users. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMANIA (RRID:SCR_005709) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/webservices/whatizit/info.jsf

A text processing system that allows you to do textmining tasks on text. It is great at identifying molecular biology terms and linking them to publicly available databases. Whatizit is also a Medline abstracts retrieval/search engine. Instead of providing the text by Copy&Paste, you can launch a Medline search. The abstracts that match your search criteria are retrieved and processed by a pipeline of your choice. Whatizit is also available as 1) a webservice and as 2) a streamed servlet. The webservice allows you to enrich content within your website in a similar way as in the wikipedia. The streamed servlet allows you to process large amounts of text.

Proper citation: Whatizit (RRID:SCR_005824) Copy   

•   Source: SciCrunch Registry

http://umbbd.msi.umn.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms).

Proper citation: UM-BBD (RRID:SCR_005787) Copy   

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http://www.molgen.de

The research of the group concentrates on the molecular biology of Gram-positive bacteria, with Bacillus subtilis and Lactococcus lactis as the main model organisms. A number of important (human) pathogens are also investigated: Bacillus cereus, Streptococcus pneumoniae and Enterococcus faecalis. The nature of the research is both fundamental and application-oriented. Transcript- and protein profiling by high-throughput technologies such as DNA microarrays and proteomics tools are being used. The very large data sets generated are analyzed by employing existing and novel bioinformatics tools. Major lines of research are in the field of functional genomics of these organisms, using systems- and synthetic biology approaches.

Proper citation: MolGen (RRID:SCR_005700) Copy   

•   Source: SciCrunch Registry

http://www.dbfordummies.com/go.asp

Db for Dummies! is a small database that imports the Generic GO Slim. It allows data to be viewed in a tree. The Gene Ontology describes gene products in terms of their associated biological processes, cellular components and molecular functions. The Generic Slim Gene Ontology is a subset of the whole Gene Ontology. The slim version gives a broad overview and leaves out specific/fine grained terms. This example stores the slim version of the Gene Ontology (goslim_generic_obo) that can be downloaded from www.geneontology.org/GO.slims.shtml. Platform: Windows compatible

Proper citation: DBD - Slim Gene Ontology (RRID:SCR_005728) Copy   

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

In the annotation world, the same piece of information can be stored and viewed differently across different databases. For instance, more than one Affymetrix probe ID can refer to the same GenBank sequence (accession number) and more than one nucleotide sequence from GenBank can be grouped in a single UniGene cluster. The result of Onto-Express depends on whether the input list contains Affymetrix probe IDs, GenBank accession numbers or UniGene cluster IDs. The user has to be aware of relations between the different forms of the data in order to interpret correctly the results. Even if the user is aware of the relationships and knows how to convert them, most existing tools allow conversions of individual genes. Onto-Translate is a tool that allows the user to perform easily such translations. Affymetrix probe IDs, etc., translate GO terms into other identifiers like GenBank accession number, Uniprot IDs. User account required. Platform: Online tool

Proper citation: Onto-Translate (RRID:SCR_005725) Copy   

•   Source: SciCrunch Registry

http://www.arabidopsis.org/servlets/Search?type=keyword&action=new_search

TAIR Keyword Browser searches and browses for Gene Ontology, TAIR Anatomy, and TAIR Developmental stage terms, and allows you to view term details and relationships among terms. It includes links to genes, publications, microarray experiments and annotations associated with the term or any children terms. Platform: Online tool

Proper citation: TAIR Keyword Browser (RRID:SCR_005687) Copy   

•   Source: SciCrunch Registry

http://www.gotaxexplorer.de/

GOTaxExplorer presents a new approach to comparative genomics that integrates functional information and families with the taxonomic classification. It integrates UniProt, Gene Ontology, NCBI Taxonomy, Pfam and SMART in one database. GOTaxExplorer provides four different query types: selection of entity sets, comparison of sets of Pfam families, semantic comparison of sets of GO terms, functional comparison of sets of gene products. This permits to select custom sets of GO terms, families or taxonomic groups. For example, it is possible to compare arbitrarily selected organisms or groups of organisms from the taxonomic tree on the basis of the functionality of their genes. Furthermore, it enables to determine the distribution of specific molecular functions or protein families in the taxonomy. The comparison of sets of GO terms allows to assess the semantic similarity of two different GO terms. The functional comparison of gene products makes it possible to identify functionally equivalent and functionally related gene products from two organisms on the basis of GO annotations and a semantic similarity measure for GO. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOTaxExplorer (RRID:SCR_005720) Copy   

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

Onto-Miner (OM) provides a single and convenient interface that allows the user to interrogate our databases regarding annotations of known genes. OM will return all known information about a given list of genes. Advantages of OM include the fact it allows queries with multiple genes and allows for scripting. This is unlike GenBank which uses a single gene navigation process. Scripted search of the Onto-Tools database for gene annotations. User account required. Platform: Online tool

Proper citation: Onto-Miner (RRID:SCR_005722) Copy   

•   Source: SciCrunch Registry

http://mcbc.usm.edu/gofetcher/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: Quick Search, Advanced Search, and Upload Files for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format. Platform: Online tool

Proper citation: GOfetcher (RRID:SCR_005681) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/gofish/GoFishWelcome.html

Software program, available as a Java applet online or to download, allows the user to select a subset of Gene Ontology (GO) attributes, and ranks genes according to the probability of having all those attributes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GoFish (RRID:SCR_005682) Copy   

•   Source: SciCrunch Registry

http://www.hcvdb.org/

The Hepatitis C Virus Database (HCVdb) is a cooperative project of several groups with the mission of providing to the scientific community studying the hepatitis C virus a comprehensive battery of informational and analytical tools. The Viral Bioinformatics Resource Center (VBRC), the Immune Epitope Database and Analysis Resource (IEDB), the Broad Institute Microbial Sequencing Center (MSC), and the Los Alamos HCV Sequence Database (HCV-LANL) are combining forces to acquire and annotate data on Hepatitis C virus, and to develop and utilize new tools to facilitate the study of this group of organisms.

Proper citation: Hepatitis C Virus Database (HCVdb) (RRID:SCR_005718) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/~nigam/cgi-bin/dokuwiki/doku.php?id=clench

Cluster Enrichment (CLENCH) allows A. thaliana researchers to perform automated retrieval of GO annotations from TAIR and calculate enrichment of GO terms in gene group with respect to a reference set. Before calculating enrichment, CLENCH allows mapping of the returned annotations to arbitrary coarse levels using GO slim term lists (which can be edited by the user) and a local installation of GO. Platform: Windows compatible, Linux compatible,

Proper citation: CLENCH (RRID:SCR_005735) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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://ccr.coriell.org/Sections/Collections/NIGMS/?SsId=8

Highly characterized cell lines and high quality DNA for cell and genetic research representing a variety of disease states, chromosomal abnormalities, apparently healthy individuals and many distinct human populations. The NIGMS Repository contains more than 10,600 cell lines, primarily fibroblasts and transformed lymphoblasts, and over 5,500 DNA samples. The NIGMS Repository has a major emphasis on heritable diseases and chromosomally aberrant cell lines. In addition, it contains a large collection dedicated to understanding human variation that includes samples from populations around the world, the CEPH collection, the Polymorphism Discovery Resource, and many apparently healthy controls. Human induced pluripotent stem cell lines, many of which were derived from NIGMS Repository fibroblasts, have recently become available through the NIGMS Repository. Sample donation facilitates all areas of research by making available well-characterized materials to any qualified researcher who might have otherwise been unable to invest the time and resources to collect needed samples independently. Donations to the Repository have created a resource of unparalleled scope. Samples from the collection have been used in more than 5,500 publications and are distributed to scientists in more than 50 countries. This resource is continuously expanding to support new directions in human genetics.

Proper citation: NIGMS Human Genetic Cell Repository (RRID:SCR_004517) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://galton.uchicago.edu/~junzhang/LAPSTRUCT.html

Software application to describe population structure using biomarker data ( typically SNPs, CNVs etc.) available in a population sample. The main features different from PCA are: (1) geometrically motivated and graphic model based; (2)robustness of outliers. (entry from Genetic Analysis Software)

Proper citation: LAPSTRUCT (RRID:SCR_007550) Copy   

•   Source: SciCrunch Registry

http://nt-salkoff.wustl.edu/portal/hgxpp001.aspx?2

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. Supplies potassium channel cDNA clones in vectors suitable for functional expression and stocks of gene knockout strains. Supporting this resource base are studies showing the basic biophysical properties of the channels, studies showing the phenotypes of mutants, and information on the cell-type expression patterns of potassium channels. Studies of potassium channel cell-type expression patterns and functional properties; studies of behavioral phenotypes; generation of knockout mutants. Full-length cDNAs encoding C. elegans potassium channels in a vector suitable for functional expression in Xenopus oocytes and mammalian cell lines are available on request. Information is also provided describing the cell-type expression patterns and basic biophysical properties of potassium channels. And data on behavioral phenotypes are also available. C. elegans strains carrying knockouts of potassium channels are also generated and deposited at the C. elegans stock center at the University of Minnesota.

Proper citation: A Comprehensive Resource Base for C. elegans K+ Channels (RRID:SCR_008360) Copy   

•   Source: SciCrunch Registry

http://www.pedigree-draw.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 12,2024. Software application for pedigree drawing (entry from Genetic Analysis Software)

Proper citation: Pedigree-Draw (RRID:SCR_008302) Copy   

•   Source: SciCrunch Registry