Searching across hundreds of databases

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

  • Register
Forgot Password

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


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.

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



Type in a keyword to search

Filter by last modified time
See new records

Current Facets and Filters

  • Availability:2016. (facet)
  • Keywords:disease (facet)
  • Website Status : Ascending


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

17 Results - per page

Resource NameResource TypeDescriptionKeywordsResource IDProper CitationParent OrganizationRelated ConditionFunding AgencyRelationReferenceWebsite StatusAlternate IDsAlternate URLsOld URLs
WD repeat Family of ProteinsResource, data or information resource, databaseTHIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. This website contains a library of WD-repeat containing proteins in which the repeats appear as multi-aligned sets. WD-repeat-containing proteins are those that contain 4 or more copies of the WD-repeat (tryptophan-aspartate repeat), a sequence motif approximately 31 amino acids long, that encodes a structural repeat. This repeat is described by the following profile, where x is ANY amino acid. By clicking on each high-lighted character you will obtain the distribution of amino acids found at that position of the repeat among an aligned set of WD-repeat containing proteins. The tertiary structure of only one member of this family has been determined, that of the G protein beta subunit, which contains 7 WD-repeats. Each of the 7 repeats folds into a small antiparallel beta-sheet. The over-lines above indicate the position of these strands, with a being the strand closest to the central pore and d at the external surface of the folded protein. These sheets are arranged around a central pseudosymmetry axis into a beta propeller. The WD-repeat-containing proteins form a very large family that is diverse in both its function and domain structure. Within all these proteins the WD-repeat domains are thought to have two common features: the domain folds into a beta propeller; and the domains form a platform without any catalytic activity on which multiple protein complexes assemble reversibly. The fact that these proteins play such key roles in the formation of protein-protein complexes in nearly all the major pathways and organelles unique to eukaryotic cells has two important implications. It supports both their ancient and proto eukaryotic origins and supports a likely association with many genetic diseases.eukaryotic, function, genetic, align, amino acid, ancient, antiparallel, aspartate, beta, cell, disease, domain, g protein, multi-aligned, organelle, origin, pathway, propeller, protein, proto, pseudosymmetry, sheet, structural, tertiary, tryptophan, wd-repeatSCR_002160(WD repeat Family of Proteins, RRID:SCR_002160)Last checked downnif-0000-20949
Sequence Tag Alignment and Consensus Knowledgebase DatabaseResource, data processing software, database, software application, data visualization software, software resource, data or information resourceTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The STACKdb is knowledgebase generated by processing EST and mRNA sequences obtained from GenBank through a pipeline consisting of masking, clustering, alignment and variation analysis steps. The STACK project aims to generate a comprehensive representation of the sequence of each of the expressed genes in the human genome by extensive processing of gene fragments to make accurate alignments, highlight diversity and provide a carefully joined set of consensus sequences for each gene. The STACK project is comprised of the STACKdb human gene index, a database of virtual human transcripts, as well as stackPACK, the tools used to create the database. STACKdb is organized into 15 tissue-based categories and one disease category. STACK is a tool for detection and visualization of expressed transcript variation in the context of developmental and pathological states. The data system organizes and reconstructs human transcripts from available public data in the context of expression state. The expression state of a transcript can include developmental state, pathological association, site of expression and isoform of expressed transcript. STACK consensus transcripts are reconstructed from clusters that capture and reflect the growing evidence of transcript diversity. The comprehensive capture of transcript variants is achieved by the use of a novel clustering approach that is tolerant of sub-sequence diversity and does not rely on pairwise alignment. This is in contrast with other gene indexing projects. STACK is generated at least four times a year and represents the exhaustive processing of all publicly available human EST data extracted from GenBank. This processed information can be explored through 15 tissue-specific categories, a disease-related category and a whole-body indexexonic, expressed, expressed sequence tag (est), expression, fragment, gene, alignment, alternative gene, cdna, clone, cluster, developmental, disease, diversity, genome, homo sapiens, human, isoform, knowledgebase, meta-cluster, mrna, pathological, sequence, tissue, transcript, variant, visualizationSCR_002156(Sequence Tag Alignment and Consensus Knowledgebase Database, RRID:SCR_002156)Last checked downnif-0000-20946
AceViewResource, data or information resource, databaseTHIS RESOURCE IS NO LONGER SUPPORTED, documented August 29, 2016. AceView offers an integrated view of the human, nematode and Arabidopsis genes reconstructed by co-alignment of all publicly available mRNAs and ESTs on the genome sequence. Our goals are to offer a reliable up-to-date resource on the genes and their functions and to stimulate further validating experiments at the bench. AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals' transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated. Our goals are to offer an up-to-date resource on the genes, in the hope to stimulate further experiments at the bench, or to help medical research. AceView can be queried by meaningful words or groups of words as well as by most standard identifiers, such as gene names, Entrez Gene ID, UniGene ID, GenBank accessions.est, exon, expression, function, gene, alignment, arabidopsis, cdna, co-alignment, coding, disease, genome, genomic, human, intron, localization, mammal, mouse, mrna, nematode, pathway, phenotype, plant, polyadenylation, promoter, rat, sequence, signal, tissue, transcript, transcriptome, worm, blast, gold standardSCR_002277(AceView, RRID:SCR_002277)NCBI Last checked downnif-0000-21007
GenomEUtwinResource, disease-related portal, topical portal, database, biomaterial supply resource, research forum portal, portal, material resource, data or information resourceTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Study of genetic and life-style risk factors associated with common diseases based on analysis of European twins. The population cohorts used in the Genomeutwin study consist of Danish, Finnish, Italian, Dutch, English, Australian and Swedish twins and the MORGAM population cohort. This project will apply and develop new molecular and statistical strategies to analyze unique European twin and other population cohorts to define and characterize the genetic, environmental and life-style components in the background of health problems like obesity, migraine, coronary heart disease and stroke, representing major health care problems worldwide. The participating 8 twin cohorts form a collection of over 0.6 million pairs of twins. Tens of thousands of DNA samples with informed consents for genetic studies of common diseases have already been stored from these population-based twin cohorts. Studies targeted to cardiovascular traits are now being undertaken in MORGAM, a prospective case-cohort study. MORGAM cohorts include approximately 6000 individuals, drawn from population-based cohorts consisting of more than 80 000 participants who have donated DNA samples.genetic, environment, lifestyle, gene, diseaseSCR_002843(GenomEUtwin, RRID:SCR_002843)University of Helsinki; Helsinki; Finland TwinEuropean Unionrelated to: KI Biobank - TwinGene, listed by: One Mind Biospecimen Bank ListingLast checked downnif-0000-25218
International HapMap ProjectResource, narrative resource, data or information resource, experimental protocol, databaseTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.genetic variant, disease, genetic sequence, genetic variation, single nucleotide polymorphism, genetic diversity, dna, sequence, catalog, genome, chromosomeSCR_002846(International HapMap Project, RRID:SCR_002846)NCBI Chinese Academy of Sciences, Chinese Ministry of Science and Technology, Delores Dore Eccles Foundation, Genome Canada, Genome Quebec, Hong Kong Innovation and Technology Commission, Japanese Ministry of Education Culture Sports Science and Technology MEXT, National Natural Science Foundation of China, NIH, SNP Consortium, University Grants Committee of Hong Kong, Wellcome Trust, W. M. Keck Foundationrelated to: SNAP - SNP Annotation and Proxy Search, Haploview, NHGRI Sample Repository for Human Genetic Research, DistiLD - Diseases and Traits in LD, SNP at Ethnos, GBrowse, used by: BioSample Database at EBI, listed by: OMICtoolsLast checked downnif-0000-02940, OMICS_00273
OBD-PKB InterfaceResource, ontology, data or information resource, controlled vocabularyTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. This interface is for exploring data collected as part of the NIF Neurodegenerative Disease Ontology project. Not generally intended for public consumption yet, but people are welcome to look - large caveat emptor applies. Sponsors: This resource is part of the NIF, disease, neurodegenerative, softwareSCR_002882(OBD-PKB Interface, RRID:SCR_002882)University of California; Berkeley; USA Last checked downnif-0000-25570
Allen Institute NeurowikiResource, wiki, data or information resource, database, narrative resource, ontology, controlled vocabularyTHIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016. The Allen Institute Neurowiki is a joint project between Vulcan Inc. and the Allen Institute to build a Semantic Wiki mapping genetic instances. It is a finished prototype testing the import pipelines and display componenets for combining 5 major RDF datasets from 4 different sources. Current planning includes mapping complete datasets, curating a better ontology, and creating multiple ontology management for a user class. Biological Linked Data Map: * Open, public online access * Data from multiple RDF data stores * Complete import pipeline using LDIF framework * Outlines of each imported instance embedding inline wiki properties and providing views of imported properties from original RDF datasets * Charting tools that ''''pivot'''' SPARQL queries providing several views of each query * Navigation and composition tools for accessing and mining the data Where did we get the data? * KEGG: Kyoto Encyclopedia of Genes and Genomes: KEGG GENES is a collection of gene catalogs for all complete genomes generated from publicly available resources, mostly NCBI RefSeq * Diseasome: The Diseasome website is a disease / disorder relationships explorer and a sample of an innovative map-oriented scientific work. Built by a team of researchers and engineers, it uses the Human Disease Network dataset. * DrugBank: The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug data with comprehensive drug target information. * Sider: Sider contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. Every piece of content on every instance page is generated by Semantic Result Formatters interpreting SPARQL results.gene, disease, drug, effect, pathway, sparql, triplestore, probe, structureSCR_005042(Allen Institute Neurowiki, RRID:SCR_005042)Allen Institute for Brain Science related to: KEGG, Diseasome, DrugBank, SIDERLast checked downnlx_144032
UMKC Neuroscience Brain Tissue Bank and Research LaboratoryResource, biomaterial supply resource, tissue bank, service resource, brain bank, storage service resource, material resource, material storage repositoryTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 31, 2016. The UMKC Neuroscience Brain Tissue Bank and Research Laboratory has been established to obtain, process, and distribute human brain tissue to qualified scientists and clinicians dedicated to neuroscience research. No other living organ approaches the human brain in complexity or capacity. Healthy, it astounds and inspires miracles. Diseased, it confounds and diminishes hope. The use of human brain tissue for research will provide insight into the anatomical and neurochemical aspects of diseased and non-diseased brains. While animal models are helpful and necessary in understanding disease, certain disorders can be more efficiently studied using human brain tissue. Also, modern research techniques are often best applied to human tissue. We also need samples of brain tissue that have not been affected by disease. They help us to compare a 'normal' brain with a diseased one. Also, we have a critical need for brain donations from relatives who have genetically inherited disorders. Tissue preparation consists of fresh quick-frozen tissue blocks or coronal slices (nitrogen vapor frozen; custom dissection of specific anatomic regions) or formalin-fixed coronal slices (custom dissection of specific anatomic regions).brain tissue, brain, tissue, fresh quick-frozen, block, nitrogen vapor frozen, frozen, formalin-fixed, disease, normal, genetically inherited disorder, normal control, matched control, neuroscience, post-mortem, coronal sliceSCR_005148(UMKC Neuroscience Brain Tissue Bank and Research Laboratory, RRID:SCR_005148)University of Missouri-Kansas City School of Medicine; Missouri; USA Disease, Normal, Genetically inherited disorder, Normal control, Matched controllisted by: One Mind Biospecimen Bank ListingLast checked downnlx_144161
KI Biobank - STAGEResource, disease-related portal, topical portal, research forum portal, biomaterial supply resource, data set, portal, material resource, data or information resourceTHIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The Swedish twin registry has recently examined all twins in Sweden born between 1959-1985. 25,000 individuals participated in the study. The twins had to implement a Web-based survey on the Internet or a telephone interview where we had to answer questions about, among other things, about the diseases they have, or have had, behaviors, eating and drinking habits, smoking habits, etc. The aim of the study is to extend the information in the Swedish twin registry. Our goal with twin studies are, inter alia, to study the relative importance of the heritage and environment for the emergence of various diseases. The responses from the study is currently the basis for a number of analyses regarding how inheritance and environment affects disease and tobacco habits. Currently third follow-up STAGE where 10,000 twins that had previously taken part are contacted again. The purpose of alteplase randomized controlled trials is to follow up the same individuals one year after the first and second questionnaire replies were received to see if anything has changed. The issues we are interested in the follow-up to include changes in general health, working and living situation, your weight, smoking habits, etc. Study Results The results we have so far come to and which we can present here are figures on the prevalence of certain diseases. The figures give a rough estimate of the incidence of these diseases will look for all individuals, born in Sweden in 1959-1985. The figures are based on the questions on the questionnaire which the twins themselves had to answer whether they have or have had various, gene, environment, survey, interview, disease, behavior, eating habit, drinking habit, questionnaire, nicotine, smoking, nicotine use disorderSCR_006004(KI Biobank - STAGE, RRID:SCR_006004)Karolisnka Biobank Twinrelated to: Swedish Twin Registry, listed by: One Mind Biospecimen Bank ListingLast checked downnlx_151384
Rickettsia Genome DatabaseResource, image, data or information resource, databaseTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. Rickettsia are obligate intracellular bacteria living in arthropods. They occasionally cause diseases in humans. To understand their pathogenicity, physiologies and evolutionary mechanisms, RicBase is sequencing different species of Rickettsia. Up to now we have determined the genome sequences of R. conorii, R. felis, R. bellii, R. africae, and R. massiliae. The RicBase aims to organize the genomic data to assist followup studies of Rickettsia. This website contains information on R. conorii and R. prowazekii. A R. conorii and R. prowazekii comparative genome map is also available. Images of genome maps, dendrogram, and sequence alignment allow users to gain a visualization of the diagrams.evolutionary, africae, alignment, arthropod, bacteria, bellii, conorii, dendrogram, disease, genome, genomic, human, intracellular, massiliae, mechanism, pathogenicity, physiology, prowazekii, rickettsia, sequence, specie, journal article, topical portalSCR_007102(Rickettsia Genome Database, RRID:SCR_007102)Last checked downnif-0000-20993
BayGenomicsResource, biomaterial supply resource, material resource, organism supplier, tissue bankTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The BayGenomics gene-trap resource provides researchers with access to thousands of mouse embryonic stem (ES) cell lines harboring characterized insertional mutations in both known and novel genes. The major goal of BayGenomics is to identify genes relevant to cardiovascular and pulmonary disease.embryonic, expression, gene, bioinformatic, cardiopulmonary, cell, clone, disease, genomic, germline, insertional, line, mouse, mutant, mutation, pulmonary, stem, cardiovascular, pulmonary diseaseSCR_008168(BayGenomics, RRID:SCR_008168)University of California at San Francisco; California; USA listed by: One Mind Biospecimen Bank ListingLast checked downnif-0000-21042
CDKN2A DatabaseResource, data or information resource, databaseTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The CDKN2A Database presents the germline and somatic variants of the CDKN2A tumor suppressor gene recorded in human disease through June 2003, annotated with evolutionary, structural, and functional information, in a format that allows the user to either download it or manipulate it for their purposes online. The goal is to provide a database that can be used as a resource by researchers and geneticists and that aids in the interpretation of CDKN2A missense variants. Most online mutation databases present flat files that cannot be manipulated, are often incomplete, and have varying degrees of annotation that may or may not help to interpret the data. They hope to use CDKN2A as a prototype for integrating computational and laboratory data to help interpret variants in other cancer-related genes and other single nucleotide polymorphisms (SNPs) found throughout the genome. Another goal of the lab is to interpret the functional and disease significance of missense variants in cancer susceptibility genes. Eventually, these results will be relevant to the interpretation of single nucleotide polymorphisms (SNPs) in general. The CDKN2A locus is a valuable model for assessing relationships among variation, structure, function, and disease because: Variants of this gene are associated with hereditary cancer: Familial Melanoma (and related syndromes); somatic alterations play a role in carcinogenesis; allelic variants occur whose functional consequences are unknown; reliable functional assays exist; and crystal structure is known. All variants in the database are recorded according to the nomenclature guidelines as outlined by the Human Genome Variation Society. This database is currently designed for research purposes only and is not yet recommended as a clinical resource. Many of the mutations reported here have not been tested for disease association and may represent normal, non-disease causing polymorphisms.evolutionary, familial, function, functional, gene, gene-, genetic, allele, allelic, alteration, cancer, carcinogenesis, cdkn2a, crystal, disease, genome, germline, hereditary, human, locus, melanoma, missense, model, mutation, nucleotide, or disease- specific databases, polymorphism, single, snp, somatic, structural, structure, suppressor, syndrome, system-, tumor, variant, variationSCR_008179(CDKN2A Database, RRID:SCR_008179)University of Vermont; Vermont; USA Last checked downnif-0000-21079
Candidate Genes to Inherited DiseasesResource, data analysis service, production service resource, analysis service resource, database, service resource, data or information resourceTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A database of candidate genes for mapped inherited human diseases. Candidate priorities are automatically established by a data mining algorithm that extracts putative genes in the chromosomal region where the disease is mapped, and evaluates their possible relation to the disease based on the phenotype of the disorder. Data analysis uses a scoring system developed for the possible functional relations of human genes to genetically inherited diseases that have been mapped onto chromosomal regions without assignment of a particular gene. Methodology can be divided in two parts: the association of genes to phenotypic features, and the identification of candidate genes on a chromosonal region by homology. This is an analysis of relations between phenotypic features and chemical objects, and from chemical objects to protein function terms, based on the whole MEDLINE and RefSeq databases.function, gene, genetic, chromosome, disease, disorder, genome, homology, human, phenotype, protein, region, candidate gene, database, data warehouse, data setSCR_008190(Candidate Genes to Inherited Diseases, RRID:SCR_008190) EMBL - Bork Group , European Molecular Biology Laboratory related to: Gene Ontology, listed by: 3DVC, Gene Ontology ToolsPMID:16115313Last checked downnif-0000-21162,
LitMinerResource, data or information resource, databaseTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The LitMiner software is a literature data-mining tool that facilitates the identification of major gene regulation key players related to a user-defined field of interest in PubMed abstracts. The prediction of gene-regulatory relationships is based on co-occurrence analysis of key terms within the abstracts. LitMiner predicts relationships between key terms from the biomedical domain in four categories (genes, chemical compounds, diseases and tissues). The usefulness of the LitMiner system has been demonstrated recently in a study that reconstructed disease-related regulatory networks by promoter modeling that was initiated by a LitMiner generated primary gene list. To overcome the limitations and to verify and improve the data, we developed WikiGene, a Wiki-based curation tool that allows revision of the data by expert users over the Internet. It is based on the annotation of key terms in article abstracts followed by statistical co-citation analysis of annotated key terms in order to predict relationships. Key terms belonging to four different categories are used for the annotation process: -Genes: Names of genes and gene products. Gene name recognition is based on Ensembl . Synonyms and aliases are resolved. -Chemical Compounds: Names of chemical compounds and their respective aliases. -Diseases and Phenotypes: Names of diseases and phenotypes -Tissues and Organs: Names of tissues and organs LitMiner uses a database of disease and phenotype terms for literature annotation. Currently, there are 2225 diseases or phenotypes, 801 tissues and organs, and 10477 compounds in the database.gene, biomedical, chemical, compound, disease, identification, literature, medline interfaces, mining, modeling, phenotype, promoter, regulation, regulatory, relationship, tissue, toolSCR_008200(LitMiner, RRID:SCR_008200)Last checked downnif-0000-21241
Centre for Visual SciencesResource, laboratory portal, portal, organization portal, data or information resourceTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Vision Science is a large discipline at the ANU that is found in several teaching and research faculties and several large research institutes. About 85 research staff participate in all forms of vision science from machine vision, to neurophysiology, behaviour and cognition. The scale of analysis ranges from molecular to systems approaches and covers insect, vertebrate and human visual systems. Topics such as disease and development of the human visual system are also covered. CVS works to connect and sustain the component parts of the ANU vision science community.behavior, cognition, development, disease, human, insect, molecular, neurophysiology, research, science, system, vertebrate, vision, visualSCR_008324(Centre for Visual Sciences, RRID:SCR_008324)Australian National University; Acton; Australia Last checked downnif-0000-24688
IntegromeDBResource, data or information resource, databaseTHIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016. Search engine that integrates over 100 curated and publicly contributed data sources and provides integrated views on the genomic, proteomic, transcriptomic, genetic and functional information currently available. Information featured in the database includes gene function, orthologies, gene expression, pathways and protein-protein interactions, mutations and SNPs, disease relationships, related drugs and compounds.catalog, search engine, gene, protein, gene regulation, gene expression, protein-protein interaction, pathway, metagenomics, mutation, disease, transcriptional regulation, genomics, transcriptomics, genetics, function, interaction, orthologSCR_004620(IntegromeDB, RRID:SCR_004620)University of California at San Diego; California; USA NIGMS, NIHrelated to: ABS: A Database of Annotated Regulatory Binding Sites From Orthologous PromotersReferences (2)Last checked downnlx_63198
Cancer Gene IndexResource, data or information resource, databaseTHIS RESOURCE IS NO LONGER SUPPORTED, documented on November 17, 2016. A database of genes that have been experimentally associated with human cancer diseases and/or pharmacological compounds, the evidence of these associations, and relevant annotations on the data.gene, cancer, genetics, pharmacology, disease, database, dataSCR_001117(Cancer Gene Index, RRID:SCR_001117)National Cancer Institute Cancerlisted by: OMICtoolsLast checked upOMICS_01575
  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.