Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

Preparing word cloud

×

Search

Type in a keyword to search

Filter by last modified time
See new records

Current Facets and Filters

  • Funding Agency:NHGRI (facet)
  • Resource Type : Ascending

Facets

Sort alphabetically | Sort by count

Recent searches

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.

(last updated: Oct 12, 2019)

Physical Resource or Software Tool Software

190 Results - per page

Resource NameResource TypeDescriptionKeywordsResource IDProper CitationParent OrganizationRelated ConditionFunding AgencyRelationReferenceWebsite StatusAlternate IDsAlternate URLsOld URLs
Alliance of Genome Resources Organization, organization portal, consortium, service resource, portal, access service resource, data or information resourceOrganization that aims to develop and maintain sustainable genome information resources to promote understanding of the genetic and genomic basis of human biology, health, and disease. The Alliance is composed of FlyBase, Mouse Genome Database (MGD), the Gene Ontology Consortium (GOC), Saccharomyces Genome Database (SGD), Rat Genome Database (RGD), WormBase, and the Zebrafish Information Network (ZFIN).gene ontology, human biology, genome, organism model, gene ontology consortiumSCR_015850(Alliance of Genome Resources , RRID:SCR_015850)NHGRILast checked up
STARResource, algorithm resource, standalone software, data processing software, software application, sequence analysis software, data analysis software, software resourceSoftware performing alignment of high-throughput RNA-seq data. STAR is based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure.alignment, rna, rna-seq, reference, aligner, algorithm, short read, suffix, array, cluster, stitchSCR_015899(STAR, RRID:SCR_015899)NHGRIPMID:23104886Last checked up
BelvuResource, alignment software, image analysis software, data processing software, software resource, software applicationSoftware for multiple sequence alignment viewing, editing and phylogeny. It includes a set of user-configurable modes to color residues used to create high-quality reference alignments.editing, phylogeny, sequence, alignment, phylogenetic, viewer, multiple, editor, color, residue, referenceSCR_015989(Belvu, RRID:SCR_015989)Wellcome Trust Sanger Institute; Hinxton; United Kingdom NHGRI, Wellcome Trust Grantrelated to: SEQtoolsPMID:26801397Last checked up
BlixemResource, alignment software, image analysis software, data processing software, software resource, software applicationSoftware for sequence alignments that displays multiple match sequences aligned against a single genomic reference sequence. It can be used for manipulation, display and annotation of genomic data, to check the quality of an alignment, to find missing/misaligned sequence, and to identify splice sites and polyA sites.software, sequence, alignment, annotation, genomic, reference, data, display, manipulation, DNASCR_015994(Blixem, RRID:SCR_015994)Wellcome Trust Sanger Institute; Hinxton; United Kingdom NHGRI, Wellcome Trust Grantrelated to: SEQtoolsPMID:26801397Last checked up
T-profilerResource, analysis service resource, data analysis service, service resource, production service resourceOne of the key challenges in the analysis of gene expression data is how to relate the expression level of individual genes to the underlying transcriptional programs and cellular state. The T-profiler tool hosted on this website uses the t-test to score changes in the average activity of pre-defined groups of genes. The gene groups are defined based on Gene Ontology categorization, ChIP-chip experiments, upstream matches to a consensus transcription factor binding motif, and location on the same chromosome, respectively. If desired, an iterative procedure can be used to select a single, optimal representative from sets of overlapping gene groups. A jack-knife procedure is used to make calculations more robust against outliers. T-profiler makes it possible to interpret microarray data in a way that is both intuitive and statistically rigorous, without the need to combine experiments or choose parameters. Currently, gene expression data from Saccharomyces cerevisiae and Candida albicans are supported. Users can submit their microarray data for analysis by clicking on one of the two organism-specific tabs above. Platform: Online toolexpression, gene, binding, cellular, transcriptional, gene expression, microarray, gene ontology, transcription factor, binding motif, chip-chip, chip, motif, t-test, statistical analysis, transcriptomeSCR_003452(T-profiler, RRID:SCR_003452) University of Amsterdam; Amsterdam; Netherlands , Columbia University; New York; USA Netherlands Foundation for Technical Research, NHGRIrelated to: Gene Ontology, listed by: Biositemaps, Gene Ontology ToolsPMID:15980543Last checked upnif-0000-33354
bioPIXIEResource, analysis service resource, data analysis service, service resource, production service resourcebioPIXIE is a general system for discovery of biological networks through integration of diverse genome-wide functional data. This novel system for biological data integration and visualization, allows you to discover interaction networks and pathways in which your gene(s) (e.g. BNI1, YFL039C) of interest participate. The system is based on a Bayesian algorithm for identification of biological networks based on integrated diverse genomic data. To start using bioPIXIE, enter your genes of interest into the search box. You can use ORF names or aliases. If you enter multiple genes, they can be separated by commas or returns. Press ''submit''. bioPIXIE uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the bioPIXIE algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. As you move the mouse over genes in the network, interactions involving these genes are highlighted. If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed. You may need to download the Adobe Scalable Vector Graphic (SVG) plugin to utilize the visualization tool (you will be prompted if you need it).prediction, bayesian network, probabilistic, interaction, networkSCR_004182(bioPIXIE, RRID:SCR_004182)Princeton University; New Jersey; USA NHGRI, NIGMS, NSFPMID:16420673Last checked downnlx_20893
FuncAssociate: The Gene Set FunctionatorResource, analysis service resource, data analysis service, service resource, production service resourceA 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 toolgene, gene ontology, statistical analysis, web serviceSCR_005768(FuncAssociate: The Gene Set Functionator, RRID:SCR_005768)Roth Laboratory Canadian Institute for Advanced Research, NHGRI, NHLBI, NIH, NINDSrelated to: Gene Ontology, listed by: Gene Ontology Tools, OMICtoolsReferences (2)Last checked upnlx_149233, OMICS_02264http://llama.mshri.on.ca/cgi/func/funcassociate
ESEfinder 3.0Resource, analysis service resource, data analysis service, service resource, production service resourceA web-based resource that facilitates rapid analysis of exon sequences to identify putative exonic splicing enhancers (ESEs) responsive to the human SR proteins SF2/ASF, SC35, SRp40 and SRp55, and to predict whether exonic mutations disrupt such elements.exonic splicing enhancer, sr proteinSCR_007088(ESEfinder 3.0, RRID:SCR_007088)Cold Spring Harbor Laboratory NCI, NHGRI, NIGMSPMID:12824367Last checked upnif-0000-30496http://rulai.cshl.edu/tools/ESE2/http://exon.cshl.edu/ESE/
Gene Relationships Across Implicated Loci Resource, analysis service resource, data analysis service, service resource, resource, production service resourceA tool to examine relationships between genes in different disease associated loci. Given several genomic regions or SNPs associated with a particular phenotype or disease, GRAIL looks for similarities in the published scientific text among the associated genes. As input, users can upload either (1) SNPs that have emerged from a genome-wide association study or (2) genomic regions that have emerged from a linkage scan or are associated common or rare copy number variants. SNPs should be listed according to their rs#''s and must be listed in HapMap. Genomic Regions are specified by a user-defined identifier, the chromosome that it is located on, and the start and end base-pair positions for the region. Grail can take two sets of inputs - Query regions and Seed regions. Seed regions are definitely associated SNPs or genomic regions, and Query regions are those regions that the user is attempting to evaluate agains them. In many applications the two sets are identical. Based on textual relationships between genes, GRAIL assigns a p-value to each region suggesting its degree of functional connectivity, and picks the best candidate gene. GRAIL is developed by Soumya Raychaudhuri in the labs of David Altshuler and Mark Daly at the Center for Human Genetic Research of Massachusetts General Hospital and Harvard Medical School, and the Broad Institute. GRAIL is described in manuscript, currently in preparation.software, text mining, genotype, phenotype, snpSCR_008537( Gene Relationships Across Implicated Loci , RRID:SCR_008537)Broad Institute NHGRI, NIAMS, NIDDKlisted by: 3DVCPMID:19557189Last checked upnif-0000-30627
PROVEANResource, analysis service resource, software resource, data analysis service, service resource, production service resourceA software tool which predicts whether an amino acid substitution or indel has an impact on the biological function of a protein.amino acid substitution, indel, function, protein, amino acid, substitution, protein variant, genome variant, next-generation sequencing, insertion, deletionSCR_002182(PROVEAN, RRID:SCR_002182)J. Craig Venter Institute NHGRI, NIHlisted by: OMICtoolsPMID:23056405Last checked upOMICS_01849
Primer3Resource, analysis service resource, software resource, data analysis service, service resource, production service resourceTool used to design PCR primers from DNA sequence - often in high-throughput genomics applications. It does everything from mispriming libraries to sequence quality data to the generation of internal oligos.primer, primer design, polymerase chain reaction, pcr primer, dna sequence, c, perlSCR_003139(Primer3, RRID:SCR_003139)University of Tartu; Tartu; Estonia NHGRIrelated to: Primer3Plus, Primer-BLAST, listed by: OMICtoolsReferences (2)Last checked upnlx_156833, OMICS_02325http://bioinfo.ut.ee/primer3-0.4.0/, http://sourceforge.net/projects/primer3/, http://frodo.wi.mit.edu/primer3
SRMAtlasResource, atlas, database, data or information resourceResource of targeted proteomics assays to detect and quantify proteins in complex proteome digests by mass spectrometry. Used to quantify the complete human proteome.collection, proteomic, assay, detect, quantify, protein, mass, spectrometry, peptideSCR_016996(SRMAtlas, RRID:SCR_016996)American Recovery and Reinvestment Act, European Research Council, Luxembourg Centre for Systems Biomedicine University Luxembourg, NCRR, NHGRI, NIGMS, Swiss National Science FoundationPMID:27453469Last checked up
NHGRI Sample Repository for Human Genetic ResearchResource, biomaterial supply resource, material resource, cell repositoryDNA samples and cell lines from fifteen populations, including the samples used for the International HapMap Project, the HapMap 3 Project and the 1000 Genomes Project (except for the CEPH samples). All of the samples were contributed with consent to broad data release and to their use in many future studies, including for extensive genotyping and sequencing, gene expression and proteomics studies, and all other types of genetic variation research. NHGRI led the contribution of the NIH to the International HapMap Project, which developed a haplotype map of the human genome. This haplotype map, called the HapMap is a publicly available tool that allows researchers to find genes and genetic variations that affect health and disease. The samples from four populations used to develop the HapMap were initially housed in the Human Genetic Cell Repository of the National Institute of General Medical Sciences (NIGMS). Except for the Utah CEPH samples that were in the NIGMS Repository before the initiation of the HapMap Project and remain there, the NHGRI Repository now houses all of the HapMap samples. The NHGRI repository also houses the extended set of HapMap samples, which includes additional samples from the HapMap populations and samples from seven additional populations. All of the samples were collected with extensive community engagement, including discussions with members of the donor communities about the ethical and social implications of human genetic variation research. These samples were studied as part of the HapMap 3 Project. The NHGRI repository also houses the samples for the International 1000 Genomes Project. This Project is lightly sequencing genome-wide 2500 samples from 27 populations. This project aims to provide a detailed map of human genetic variation, including common and rare SNPs and structural variants. This map will allow more precise localization of genomic regions that contribute to health and disease. The 1000 Genomes Project includes many of the samples from the HapMap and extended set of HapMap samples, as well as samples being collected from additional populations. Currently, samples from five additional populations are available; the others will become available during 2011 and 2012. No identifying or phenotypic information is available for the samples. Donors gave broad consent for use of the samples, including for genotyping, sequencing, and cellular phenotype studies. Samples collected from other populations for the study of human genetic variation may be added to the collection in the future. The NHGRI Repository distributes high quality lymphoblastoid cell lines and DNA from the samples to researchers. DNA is provided in plates or panels of 70 to 100 samples or as individual samples. Cell cultures and DNA samples are distributed only to qualified professional persons who are associated with recognized research, medical, educational, or industrial organizations engaged in health-related research or health delivery.genome, frozen, gene, dna, cell line, lymphoblastoid cell line, genetic variationSCR_004528(NHGRI Sample Repository for Human Genetic Research, RRID:SCR_004528)Coriell Cell Repositories AllNHGRIrelated to: International HapMap Project, HapMap 3 and ENCODE 3, used by: 1000 Genomes: A Deep Catalog of Human Genetic Variation, listed by: One Mind Biospecimen Bank ListingLast checked upnlx_143818
GWAS: Catalog of Published Genome-Wide Association StudiesResource, catalog, data or information resource, databaseCatalog of published genome-wide association studies. Genome-wide set of genetic variants in different individuals to see if any variant is associated with trait and disease. Database of genome-wide association study (GWAS) publications including only those attempting to assay single nucleotide polymorphisms (SNPs). Publications are organized from most to least recent date of publication. Studies are identified through weekly PubMed literature searches, daily NIH-distributed compilations of news and media reports, and occasional comparisons with an existing database of GWAS literature (HuGE Navigator).gene-wide association study, adult, genome, genome-wide association study, single nucleotide polymorphism, publication, literature, phenotype, trait, disease, loci, genetic variant, disorder, snp trait associationSCR_012745(GWAS: Catalog of Published Genome-Wide Association Studies, RRID:SCR_012745)National Human Genome Research Institute BBSRC, NHGRIrelated to: PheWAS Catalog, Psychiatric Genomics Consortium, KOBAS, used by: NIF Data Federation, Monarch Initiative, Schizo-PiPMID:19474294Last checked upnif-0000-06666http://www.genome.gov/gwastudies
iToolsResource, data access protocol, database, web service, software repository, service resource, storage service resource, software resource, data repository, data or information resourceAn infrastructure for managing of diverse computational biology resources - data, software tools and web-services. The iTools design, implementation and meta-data content reflect the broad NCBC needs and expertise (www.NCBCs.org).computational neuroscience, data, experiment control, hardware, imaging genomics, information specification, java, loni pipeline, model, ontology, os independent, metadataSCR_009626(iTools, RRID:SCR_009626)Laboratory of Neuro Imaging NCI, NCRR, NHGRI, NIBIB, NIDA, NIGMS, NIH Roadmap for Medical Research, NLMrelated to: National Centers for Biomedical Computing, listed by: NeuroImaging Tools and Resources Collaboratory (NITRC)PMID:18509477Last checked upnlx_155852http://www.nitrc.org/projects/itools, http://www.loni.usc.edu/research/softwarehttp://itools.loni.ucla.edu/
PanoramaResource, data access protocol, web service, service resource, storage service resource, software resource, data repository, data or information resourceRepository software for targeted mass spectrometry assays from Skyline. Targeted proteomics knowledge base. Public repository for quantitative data sets processed in Skyline. Facilitates viewing, sharing, and disseminating results contained in Skyline documents.repository, software, targeted, mass, spectrometry, data, proteomic, quantitative, viewing, sharing, disseminating, resultSCR_017136(Panorama, RRID:SCR_017136)University of Washington; Seattle; USA NHGRI, NIGMS, NIH, University of Washington Proteomics Resourceworks_with: SkylineDOI:10.1074/mcp.RA117.000543Last checked up
EnsemblResource, data analysis service, data access protocol, database, web service, production service resource, analysis service resource, catalog, service resource, software resource, data or information resourceCollection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.collection, genome, dataset, database, vertebrate, eukaryotic, DNA, protein, sequence, search, automaticly, annotate, dataSCR_002344(Ensembl, RRID:SCR_002344)European Bioinformatics Institute , Wellcome Trust Sanger Institute; Hinxton; United Kingdom BBSRC, EMBL, European Union, FP6, FP7, MRC, NHGRI, Wellcome Trustrelated to: Ensembl Genomes, GermOnline, CandiSNPer, Human Splicing Finder, NGS-SNP, Sanger Mouse Resources Portal, DECIPHER, Ensembl Genomes, PeptideAtlas, AnimalTFDB, Bgee: a dataBase for Gene Expression Evolution, FlyMine, Rat Gene Symbol Tracker, UniParc at the EBI, go-db-perl, UniParc, G:Profiler, RIKEN integrated database of mammals, VBASE2, p300db, used by: NIF Data Federation, Animal QTLdb, Monarch Initiative, ChannelPedia, Blueprint Epigenome, HmtPhenome, listed by: OMICtools, Biositemaps, re3data.org, LabWorm, works_with: Genotate, CellPhoneDB, Open Regulatory Annotation DatabaseReferences (2)Last checked upnif-0000-21145, OMICS_01647
GeneSigDBResource, data analysis service, data access protocol, database, web service, production service resource, analysis service resource, service resource, storage service resource, software resource, data repository, data or information resourceDatabase of traceable, standardized, annotated gene signatures which have been manually curated from publications that are indexed in PubMed. The Advanced Gene Search will perform a One-tailed Fisher Exact Test (which is equivalent to Hypergeometric Distribution) to test if your gene list is over-represented in any gene signature in GeneSigDB. Gene expression studies typically result in a list of genes (gene signature) which reflect the many biological pathways that are concurrently active. We have created a Gene Signature Data Base (GeneSigDB) of published gene expression signatures or gene sets which we have manually extracted from published literature. GeneSigDB was creating following a thorough search of PubMed using defined set of cancer gene signature search terms. We would be delighted to accept or update your gene signature. Please fill out the form as best you can. We will contact you when we get it and will be happy to work with you to ensure we accurately report your signature. GeneSigDB is capable of providing its functionality through a Java RESTful web service.gene, gene signature, curated gene signature, gene expression, gene expression signatureSCR_013275(GeneSigDB, RRID:SCR_013275)Dana-Farber Cancer Institute , Computational Biology and Functional Genomics Laboratory at Harvard CancerClaudia Adams Barr Foundation, Dana-Farber Cancer Institute, Genome Research Institute, NCI, NHGRI, NLM, Women's Cancers ProgramPMID:22110038Last checked upnlx_149342
FlyMineResource, data analysis service, data access protocol, production service resource, analysis service resource, database, web service, service resource, software resource, data or information resourceAn integrated database of genomic, expression and protein data for Drosophila, Anopheles, C. elegans and other organisms. You can run flexible queries, export results and analyze lists of data. FlyMine presents data in categories, with each providing information on a particular type of data (for example Gene Expression or Protein Interactions). Template queries, as well as the QueryBuilder itself, allow you to perform searches that span data from more than one category. Advanced users can use a flexible query interface to construct their own data mining queries across the multiple integrated data sources, to modify existing template queries or to create your own template queries. Access our FlyMine data via our Application Programming Interface (API). We provide client libraries in the following languages: Perl, Python, Ruby and & Java APIanopheles, genome, c. elegans, drosophila, gene, chromosomal location, genomics, proteomics, gene expression, interaction, homology, function, regulation, protein, phenotype, pathway, disease, publicationSCR_002694(FlyMine, RRID:SCR_002694)University of Cambridge; Cambridge; United Kingdom NHGRI, Wellcome Trustrelated to: FlyBase, Universal Protein Resource, Ensembl, InterPro, BioGRID, Research Collaboratory for Structural Bioinformatics Protein Data Bank, Tree families database, IntAct, Gene Ontology, GOA, ArrayExpress, REDfly Regulatory Element Database for Drosophilia, KEGG, ReactomePMID:17615057Last checked upnif-0000-02845
PathwayNetResource, data analysis service, data access protocol, production service resource, analysis service resource, web service, service resource, software resourceWeb user interface for interaction predictions of human gene networks and integrative analysis of user data types that takes advantage of data from diverse tissue and cell-lineage origins. Predicts presence of functional association and interaction type among human genes or its protein products on whole genome scale. Used to analyze experimetnal gene in context of interaction networks.Interface, interaction, predict, human, gene, network, integrative, analysis, user, data, tissue, cell, functional, protein, genomeSCR_017353(PathwayNet, RRID:SCR_017353)Princeton University; New Jersey; USA NHGRI, NIGMSlisted by: OMICtoolsPMID:25431329Last checked up
X
  1. RRID Portal Resources

    Welcome to the RRID Resources search. From here you can search through a compilation of resources used by RRID and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that RRID has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.

  3. Logging in and Registering

    If you have an account on RRID then you can log in from here to get additional features in RRID such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Collections

    If you are logged into RRID you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  6. Facets

    Here are the facets that you can filter the data by.

  7. Further Questions

    If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.