Tools   Select Another Resource Report Type

http://pga.mgh.harvard.edu/primerbank/

Database of human and mouse primer pairs for gene expression analysis by polymerase chain reaction (PCR) and quantitative PCR (qPCR). A total of 306,800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as T(m), location on the transcript and amplicon size. For each gene, at least one primer pair has been designed and in many cases alternative primer pairs exist. Primers have been designed to work under the same PCR conditions, thus facilitating high-throughput QPCR. All primers in PrimerBank were carefully designed to ensure gene specificity. All experimental validation data for mouse primers are available from PrimerBank. You can submit your primers. They will be added to the database once they are properly QCd.

Proper citation: PrimerBank (RRID:SCR_006898) Copy   

•   Source: SciCrunch Registry

http://www.imgt.org/IMGTindex/IMGTgene-db.html

IMGT/GENE-DB is the comprehensive IMGT genome database for immunoglobulin (IG) and T cell receptor (TR) genes from human and mouse, and, in development, from other vertebrates. IMGT/GENE-DB is the international reference for the IG and TR gene nomenclature and works in close collaboration with the HUGO Nomenclature Committee, Mouse Genome Database and genome committees for other species. IMGT/GENE-DB allows a search of IG and TR genes by locus, group and subgroup, which are CLASSIFICATION concepts of IMGT-ONTOLOGY. Short cuts allow the retrieval gene information by gene name or clone name. Direct links with configurable URL give access to information usable by humans or programs. An IMGT/GENE-DB entry displays accurate gene data related to genome (gene localization), allelic polymorphisms (number of alleles, IMGT reference sequences, functionality, etc.) gene expression (known cDNAs), proteins and structures (Protein displays, IMGT Colliers de Perles). It provides internal links to the IMGT sequence databases and to the IMGT Repertoire Web resources, and external links to genome and generalist sequence databases. IMGT/GENE-DB manages the IMGT reference directory used by the IMGT tools for IG and TR gene and allele comparison and assignment, and by the IMGT databases for gene data annotation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: IMGT/GENE-DB (RRID:SCR_006964) Copy   

•   Source: SciCrunch Registry

http://tritrypdb.org/tritrypdb/

An integrated genomic and functional genomic database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. ''''User Comments'''' may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate. TriTrypDB provides programmatic access to its searches, via REST Web Services. The result of a web service request is a list of records (genes, ESTs, etc) in either XML or JSON format. REST services can be executed in a browser by typing a specific URL. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).

Proper citation: TriTrypDB (RRID:SCR_007043) Copy   

•   Source: SciCrunch Registry

http://www.vbase2.org/

Integrative database of germ-line V genes from the immunoglobulin loci of human and mouse. It presents V gene sequences extracted from the EMBL nucleotide sequence database and Ensembl together with links to the respective source sequences. Based on the properties of the source sequences, V genes are classified into 3 different classes: * Class 1: genomic and rearranged evidence * Class 2: genomic evidence only * Class 3: rearranged evidence only This allows careful sequence quality validation by the user. References to other immunological databases ( KABAT, IMGT/LIGM and VBASE ) are given to provide all public annotation data for each V gene. The VBASE2 database can be accessed either by the Direct Query interface or by the DNAPLOT Query interface. The Sequences given by the user are aligned with DNAPLOT against the VBASE2 database. Direct Query allows to enter sequence IDs and names (Field 1), choose species, locus, V gene family and class (Field 2) or search for 100% sequences (Field 3). At the DNAPLOT Query, the sequences given by the user are aligned with DNAPLOT against the VBASE2 database. The DNAPLOT program offers V gene nucleotide sequence alignment referring to the IMGT V gene unique numbering. The Quick Search can be used either for Direct Query to search for sequence IDs and V gene names or for DNAPLOT Query for up to 5 sequences. The new Fab Analysis allows you to align Fab, scFab, scAb or scFv sequences with DNAPLOT against the VBASE2 database, where both heavy and light chain are analyzed.

Proper citation: VBASE2 (RRID:SCR_007082) Copy   

•   Source: SciCrunch Registry

http://gene3d.biochem.ucl.ac.uk/Gene3D/

A large database of CATH protein domain assignments for ENSEMBL genomes and Uniprot sequences. Gene3D is a resource of form studying proteins and the component domains. Gene3D takes CATH domains from Protein Databank (PDB) structures and assigns them to the millions of protein sequences with no PDB structures using Hidden Markov models. Assigning a CATH superfamily to a region of a protein sequence gives information on the gross 3D structure of that region of the protein. CATH superfamilies have a limited set of functions and so the domain assignment provides some functional insights. Furthermore most proteins have several different domains in a specific order, so looking for proteins with a similar domain organization provides further functional insights. Strict confidence cut-offs are used to ensure the reliability of the domain assignments. Gene3D imports functional information from sources such as UNIPROT, and KEGG. They also import experimental datasets on request to help researchers integrate there data with the corpus of the literature. The website allows users to view descriptions for both single proteins and genes and large protein sets, such as superfamilies or genomes. Subsets can then be selected for detailed investigation or associated functions and interactions can be used to expand explorations to new proteins. The Gene3D web services provide programmatic access to the CATH-Gene3D annotation resources and in-house software tools. These services include Gene3DScan for identifying structural domains within protein sequences, access to pre-calculated annotations for the major sequence databases, and linked functional annotation from UniProt, GO and KEGG., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Gene3D (RRID:SCR_007672) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/gxa/

Gene Expression Atlas is a semantically enriched database of meta-analysis based summary statistics over a curated subset of ArrayExpress Archive, servicing queries for condition-specific gene expression patterns as well as broader exploratory searches for biologically interesting genes/samples. The EBI Gene Expression Atlas Blog discusses ideas, features and problems of creating a large scale meta-analytical atlas of gene expression from publicly available microarray data. Atlas REST API provides all the results available in the main web application in a pragmatic, easy to use form - simple HTTP GET queries as input and either JSON or XML formats as output. Gene Expression Atlas goals: 1. Provision of a statistically robust framework for integration of gene expression experiment results across different platforms at a meta-analytical level 2. A simple interface for identifying strong differential expression candidate genes in conditions of interest 3. Integration of ontologies for high quality annotation of gene and sample attributes 4. Construction of new gene expression summarized views, with a view to analysis of putative signaling pathway targets, discovery of correlated gene expression patterns and the identification of condition/tissue-specific patterns of gene expression.

Proper citation: Gene Expression Atlas (RRID:SCR_007989) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/info/docs/tools/vep/index.html

Data analysis service to predict the functional consequences of known and unknown variants.

Proper citation: Variant Effect Predictor (RRID:SCR_007931) Copy   

•   Source: SciCrunch Registry

http://etest.vbi.vt.edu/etblast3/

eTBLAST is a unique search engine for searching biomedical literature. Our service is very different from PubMed. While PubMed searches for keywords, our search engine lets you input an entire paragraph and returns MEDLINE abstracts that are similar to it. This is something like PubMed''s Related Articles feature, only better because it runs on your unique set of interests. For example, input the abstract of an unpublished paper or a grant proposal into our engine, and with the touch of a button you''ll be able to find every abstract in MEDLINE dealing with your topic. No more guessing whether your set of keywords has found all the right papers. No more sorting through hundreds of papers you don''t care about to find the handful you were looking for--our search engine does it for you. When most people use PubMed to search MEDLINE they pick one or two keywords to describe their topic, then browse through a long list of results. When they find a paper that looks interesting they click on its Related Articles, in hopes of finding more papers like that one. If they find another relevant paper, they explore it''s related articles--and so on. This process of culling long lists of documents by hand makes literature searching tedious and time consuming. We make it easier for you by providing better results the first time, and then allowing you to automatically combine the papers you care about for a second round. Our Iterate feature allows you to checkmark the abstracts you found interesting in the first round and combine them all to create a new query. It''s like rolling several Related Articles lists into one. * We sort our results by relevance, while PubMed sorts by date. * We save you the time and effort of creating a complicated query. * We let you iterate your search over several good papers to narrow your focus. * We provide you the full MEDLINE abstract in our results, and a link to the PubMed page. * We can send your results straight to your email so you never lose a reference or forget where you found it. * This absolutely free service is provided by the University of Texas Southwestern Medical Center. No registration necessary!

Proper citation: eTBlast (RRID:SCR_008188) Copy   

•   Source: SciCrunch Registry

http://ophid.utoronto.ca/navigator/

A software package for visualizing and analyzing protein-protein interaction networks. NAViGaTOR can query OPHID / I2D - online databases of interaction data - and display networks in 2D or 3D. To improve scalability and performance, NAViGaTOR combines Java with OpenGL to provide a 2D/3D visualization system on multiple hardware platforms. NAViGaTOR also provides analytical capabilities and supports standard import and export formats such as GO and the Proteomics Standards Initiative (PSI). NAViGaTOR can be installed and run on Microsoft Windows, Linux / UNIX, and Mac OS systems. NAViGaTOR is written in Java and uses JOGL (Java bindings for OpenGL) to support scalability, highlighting or suppressing of information, and other advanced graphic approaches.

Proper citation: Network Analysis, Visualization and Graphing TORonto (RRID:SCR_008373) Copy   

•   Source: SciCrunch Registry

http://lowelab.ucsc.edu/tRNAscan-SE

Web server to search for tRNA genes in genomic sequence. If you would like to run tRNAscan-SE locally, you can get the UNIX source code (gzip''d tar file).

Proper citation: tRNAscan-SE (RRID:SCR_008637) Copy   

•   Source: SciCrunch Registry

http://www.nematodes.org/nematodegenomes/index.php/Main_Page

A collaborative wiki that collates information on completed, ongoing and planned genome and transcriptome sequencing projects on species from phylum Nematoda. The intention is to encourage genome sequencing across the diversity of the phylum Nematoda. Wiki includes: * Published complete nematode genomes: A dynamically generated table of all species for which the genome is published. * Nematode species with genomes in progress: A dynamically generated table of all species for which a genome project is underway. Users may add species to the list * Proposed nematode genome projects: To propose a species for genome sequencing, edit its species page, and set the genome project status to proposed. * BLAST server: Search a number of the nematode-genomes-in-progress with genes of your choice. Currently there are 12 draft genomes available... * Genomes with Data available: Genomes with data available for download. Users may add more data URLs to strain pages or update the URLs.

Proper citation: 959 Nematode Genomes (RRID:SCR_006068) Copy   

•   Source: SciCrunch Registry

http://mmdb.iab.keio.ac.jp/

MMMDB, Mouse Multiple tissue Metabolome DataBase, is a freely available metabolomic database containing a collection of metabolites measured from multiple tissues from single mice. The datases are collected using a single instrument and not integrated from literatures, which is useful for capturing the holistic overview of large metabolomic pathway. Currently data from cerabra, cerebella, thymus, spleen, lung, liver, kidney, heart, pancreas, testis, and plasma are provided. Non-targeted analyses were performed by capillary electropherograms time-of-flight mass spectrometry (CE-TOFMS) and, therefore, both identified metabolites and unknown (without matched standard) peaks were uploaded to this database. Not only quantified concentration but also processed raw data such as electropherogram, mass spectrometry, and annotation (such as isotope and fragment) are provided.

Proper citation: MMMDB - Mouse Multiple tissue Metabolome DataBase (RRID:SCR_006064) Copy   

•   Source: SciCrunch Registry

http://biodev.cea.fr/interevol/

InterEvol database is designed for the analysis of co-evolution events at the interface of known structures of hetero- and homo-oligomers. The database can be search and analyzed through 3 interconnected levels of analysis: * From a Keyword or the PDB entry of a complex, you can browse: ** structural homologs for every chain in other complexes ** structural interologs for every interface ** retrieve pre-computed sequence alignments in diverse species * From 1 or 2 sequences of interacting partners: ** build 2 multiple sequence alignments with the same species ordered in each ** query the InterEvol database with alignments using profile-profile comparison method * Visualize structure vs sequence alignment at the complex interface ** A dedicated Pymol plugin is provided ** Alignment views in Pymol are interactively restricted to the residues selected at the interface

Proper citation: InterEvol database (RRID:SCR_006054) Copy   

•   Source: SciCrunch Registry

http://db-mml.sjtu.edu.cn/ICEberg/

ICEberg is an integrated database that provides comprehensive information about integrative and conjugative elements (ICEs) found in bacteria. ICEs are conjugative self-transmissible elements that can integrate into and excise from a host chromosome. An ICE contains three typical modules, integration and excision, conjugation, and regulation modules, that collectively promote vertical inheritance and periodic lateral gene flow. Many ICEs carry likely virulence determinants, antibiotic-resistant factors and/or genes coding for other beneficial traits. ICEberg offers a unique, highly organized, readily explorable archive of both predicted and experimentally supported ICE-relevant data. It currently contains details of 428 ICEs found in representatives of 124 bacterial species, and a collection of >400 directly related references. A broad range of similarity search, sequence alignment, genome context browser, phylogenetic and other functional analysis tools are readily accessible via ICEberg. ICEberg will facilitate efficient, multidisciplinary and innovative exploration of bacterial ICEs and be of particular interest to researchers in the broad fields of prokaryotic evolution, pathogenesis, biotechnology and metabolism. The ICEberg database will be maintained, updated and improved regularly to ensure its ongoing maximum utility to the research community.

Proper citation: ICEberg (RRID:SCR_006026) Copy   

•   Source: SciCrunch Registry

http://europepmc.org/

Free access to biomedical literature resources including all of PubMed and PubMed Central, agricultural abstracts (from AGRICOLA), over 4 million international life science patents abstracts, National Health Service (NHS) clinical guidelines, and is supplemented with Chinese Biological Abstracts and the Citeseer database. As well as powerful search of abstracts and full text articles, it also includes: * article citations and sort order based on citation count * data citations mined from full text articles * links to and from related databases and institutional repositories * a tool to create bibliographies linked to your ORCID * named entity recognition of keywords and text-mining-based applications showcased in Europe PMC Labs * Tools for recipients of grants from one of the Europe PMC funders to deposit full-text manuscripts and link them to those specific grants. * Web services for programmatic access to all the above bibliographic information and 50,000 grants. * Search by publication date, relevance, or the number of times an article has been cited. * Links to public databases such as UniProt, Protein Data Bank (PDBe), and the European Nucleotide Archive (ENA) are provided. * Through textmining technologies, you can highlight and browse keywords such as gene names, organisms and diseases. * Search 40,000 biomedical research grants awarded to the 18,000 PIs supported by the Europe PMC funders. * Roadtest new tools based on Europe PMC content in Europe PMC labs. * In Europe PMC plus, PIs supported by the Europe PMC funders can link grants to publication information, view article citation and download statistics, and submit manuscripts.

Proper citation: Europe PubMed Central (RRID:SCR_005901) Copy   

•   Source: SciCrunch Registry

http://polbase.neb.com/

Repository of biochemical, genetic, and structural information about DNA Polymerases. Polbase is designed to compile detailed results of polymerase experimentation, presenting them in a dynamic view to inform further research. After validation, results from references are displayed in context with relevant experimental details and are always traceable to their source publication. Polbase is connected to other resources, including PubMed, UniProt and the RCSB Protein Data Bank, to provide multi-faceted views of polymerase knowledge. In addition to a simple web interface, Polbase data is exposed for custom analysis by external software.

Proper citation: Polbase (RRID:SCR_006107) Copy   

•   Source: SciCrunch Registry

http://www.umd.be/BRCA1/

The UMD-BRCA1/BRCA2 databases have been set up in a joined national effort through the network of 16 diagnostic laboratories to provide up-to-date information about mutations of the BRCA1 and BRCA2 genes identified in patients with breast and/or ovarian cancer. These databases currently contain published and unpublished information about the BRCA1/BRCA2 mutations reported in French diagnostic laboratories. This database includes 28 references and 5530 mutations (1440 different mutations and 786 protein variants) The databases of BRCA1 and BRCA2 mutations were built using the Universal Mutation Database tool. For each mutation, information is provided at several levels: * at the gene level: exon and codon number, wild type and mutant codon, mutation event, mutation name and, * at the protein level: wild type and mutant amino acid, binding domain, affected domain. If you want to submit a mutation, please contact R. Lidereau., S. Caputo. or E. Rouleau.

Proper citation: UMD-BRCA1/ BRCA2 databases (RRID:SCR_006128) Copy   

•   Source: SciCrunch Registry

https://github.com/stamatak/standard-RAxML

Software program for phylogenetic analyses of large datasets under maximum likelihood.

Proper citation: RAxML (RRID:SCR_006086) Copy   

•   Source: SciCrunch Registry

http://ogeedb.embl.de/#summary

Online GEne Essentiality database containing genes that were tested experimentally for essentiality and their features; it also provides a set of tools to systematically explore and analyze these data. The main purpose of this project is to better understand gene essentiality by facilitating the comparisons of the differences and similarities between essential and non-essential genes. This is achieved by collecting not only experimentally tested essential and non-essential genes, but also associated gene features such as expression profiles, duplication status, conservation across species, evolutionary origins and involvement in embryonic development. We focus on large-scale experiments and complement our data with text-mining results. Genes are organized into data sets according to their sources. Genes with variable essentiality status across data sets are tagged as conditionally essential, highlighting the complex interplay between gene functions and environments. Linked tools allow the user to compare gene essentiality among different gene groups, or compare features of essential genes to non-essential genes, and visualize the results. Why is it different from existing databases? * we included both essential and non-essential genes so that we could better understand the gene essentiality by comparing the similarities and differences between the two gene sets; * we compiled a list of features for each gene, including whether they are duplicates or involved in development, the number of other homologous genes in the same genome, as well as their earliest expression stages during development. These features are keys to understand the essentiality of genes; * we also provide a set of tools to explore our data and visualize the results. For example, users can simply divide genes into two groups according to whether they are duplicates, calculate the proportion of essential genes (PE%) in each group and then visualize the results in a bar plot; or they can classify genes into multiple groups according to their earliest expression stages during evolution, compare the essentiality of genes that were expressed earlier with those were latter, and plot the results in a line chart.

Proper citation: OGEE - Online GEne Essentiality database (RRID:SCR_006080) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/PRED-GPCR/

A prediction tool for GPCR Family Classification from sequence alone based on a probabilistic method that uses family-specific profile Hidden Markov Models. The PRED-GPCR system is based on a probabilistic method that uses family specific profile HMMs in order to determine to which GPCR family a query sequence belongs or resembles. The approach proposed in this method exploits the descriptive power of profile HMMs along with an exhaustive discrimination assessment method to select only highly selective and sensitive profiles, for each family. The collection of these profiles constitutes a signature library, which is scanned, for significant matches with a given query sequence. The output report for a query sequence consists of two sections: * A ranked list of the profile HMM matches, below the selected individual motif E-value cutoff, along with their corresponding family. * A ranked list of the Combined P-values, E-values as well as the number of profiles matched for each family. To cross-evaluate your results you can browse through Swiss-Prot, Trembl, Pfam and Prosite family related entries.

Proper citation: PRED-GPCR (RRID:SCR_006196) Copy   

•   Source: SciCrunch Registry