Medical Subject Headings
How to cite this record FAIRsharing.org: MESH; Medical Subject Headings; DOI: https://doi.org/10.25504/FAIRsharing.qnkw45; Last edited: Aug. 7, 2019, 1:47 p.m.; Last accessed: May 17 2021 2:28 p.m.
Record updated: June 27, 2019, 11:25 a.m. by The FAIRsharing Team.
Edits to 'https://fairsharing.org/FAIRsharing.qnkw45' by 'The FAIRsharing Team' at 11:25, 27 Jun 2019 (approved): 'onto_disciplines' has been modified: Before: Bioinformatics Biomedical Science Life Sciences After: Bioinformatics Biomedical Science Life Sciences Ontology and Terminology Added: Ontology and Terminology Removed: 'related_standards' has been modified: Before: Robert Hoehndorf's Version of MeSH Disease Ontology After: Robert Hoehndorf's Version of MeSH Disease Ontology Cell Line Ontology Plant Ontology Added: Cell Line Ontology Plant Ontology Removed: 'supportLinks' has been modified: Before: contact form|https://support.nlm.nih.gov/ics/support/ticketnewwizard.asp?style=classic&deptID=28054&from=https://www.nlm.nih.gov/mesh/introduction.html help|http://www.ncbi.nlm.nih.gov/books/NBK3827/#pubmedhelp.Searching_by_using_t online documentation|https://www.nlm.nih.gov/mesh/meshhome.html training|http://www.nlm.nih.gov/bsd/disted/pubmed.html training|https://www.nlm.nih.gov/bsd/disted/mesh.html After: contact form|https://support.nlm.nih.gov/support/create-case/ help|http://www.ncbi.nlm.nih.gov/books/NBK3827/#pubmedhelp.Searching_by_using_t online documentation|https://www.nlm.nih.gov/mesh/meshhome.html training|http://www.nlm.nih.gov/bsd/disted/pubmed.html training|https://learn.nlm.nih.gov/documentation/training-packets/T000101112/ Added: contact form|https://support.nlm.nih.gov/support/create-case/ training|https://learn.nlm.nih.gov/documentation/training-packets/T000101112/ Removed: contact form|https://support.nlm.nih.gov/ics/support/ticketnewwizard.asp?style=classic&deptID=28054&from=https://www.nlm.nih.gov/mesh/introduction.html training|https://www.nlm.nih.gov/bsd/disted/mesh.html 'dataProcesses' has been modified: Before: After: Medical Subject Headings 2019 - Search Download Submit Added: Medical Subject Headings 2019 - Search Download Submit Removed: 'onto_domains' has been modified: Before: After: literature curation Added: literature curation Removed:
Edits to 'https://fairsharing.org/FAIRsharing.qnkw45' by 'The FAIRsharing Team' at 23:10, 23 Nov 2016 (approved): 'contactName' has been modified: Before: After: General contact Added: Removed:
|contact form||https://support.nlm.nih.gov/support/crea ...|
|online documentation||https://www.nlm.nih.gov/mesh/meshhome.ht ...|
|training||Tutoriel and webinar|
No XSD schemas defined
Conditions of Use
|Medical Subject Headings 2019 - Search||https://meshb.nlm.nih.gov/search|
Medical subject headings.
Bull Med Libr Assoc 1963
View in BioPortal.
No guidelines defined
Models and Formats
No syntax standards defined
No identifier schema standards defined
No metrics standards defined
The SpliceDisease database provides information linking RNA splicing to human disease, including the change of the nucleotide in the sequence, the location of the mutation on the gene, the reference Pubmed ID and detailed description for the relationship among gene mutations, splicing defects and diseases.
neXtProt is a comprehensive human-centric discovery platform, offering its users a seamless integration of and navigation through protein-related data.
Comparative Toxicogenomics Database
The Comparative Toxicogenomics Database (CTD) advances understanding of the effects of environmental chemicals on human health. Biocurators manually curate chemical-gene, chemical-disease, and gene-disease relationships from the scientific literature. This core data is then internally integrated to generate inferred chemical-gene-disease networks. Additionally, the core data is integrated with external data sets (such as Gene Ontology and pathway annotations) to predict many novel associations between different data types. A unique and powerful feature of CTD is the inferred relationships generated by data integration that helps turn knowledge into discoveries by identifying novel connections between chemicals, genes, diseases, pathways, and GO annotations that might not otherwise be apparent using other biological resources.
European Mouse Mutant Archive
The European Mouse Mutant Archive (EMMA) is a non-profit repository for the collection, archiving (via cryopreservation) and distribution of relevant mutant strains essential for basic biomedical research. The laboratory mouse is the most important mammalian model for studying genetic and multi-factorial diseases in man. Thus the work of EMMA will play a crucial role in exploiting the tremendous potential benefits to human health presented by the current research in mammalian genetics.
PubChem is organized as three linked databases within the NCBI's Entrez information retrieval system. These are PubChem Substance, PubChem Compound, and PubChem BioAssay. PubChem also provides a fast chemical structure similarity search tool. More information about using each component database may be found using the links in the homepage.
PubMed is a search engine of biomedical literature, provided as a service of the U.S. National Library of Medicine and includes more than 25 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.
Orphanet is the reference resource for information on rare diseases and orphan drugs for all publics. Its aim is to contribute to the improvement of the diagnosis, care and treatment of patients with rare diseases. Orphanet maintains the Orphanet nomenclature, essential for interoperability, and the Orphanet Rare Disease Ontology (ORDO).
GWAS Central stores genome-wide association study data. The database content comprises direct submissions received from GWAS authors and consortia in addition to actively gathered data sets from various public sources. GWAS data are discoverable from the perspective of genetic markers, genes, genome regions or phenotypes, via graphical visualizations and detailed downloadable data reports.
DisGeNET: a knowledge base for disease genomics
DisGeNET is a discovery platform containing one of the largest collections available of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models, and the scientific literature, and covers the whole landscape of human diseases. The current version of DisGeNET (v7.0) contains 1,134,942 gene-disease associations (GDAs), between 21,671 genes and 30,170 diseases, disorders, traits, and clinical or abnormal human phenotypes, and 369,554 variant-disease associations (VDAs), between 194,515 variants and 14,155 diseases, traits, and phenotypes. The data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, a REST API, and an R package.
UniCarbKB is an initiative that aims to promote the creation of an online information storage and search platform for glycomics and glycobiology research. The knowledgebase will offer a freely accessible and information-rich resource supported by querying interfaces, annotation technologies and the adoption of common standards to integrate structural, experimental and functional data.
The GeneWeaver data and analytics website is a publically available resource for storing, curating and analyzing sets of genes from heterogeneous data sources. The system enables discovery of relationships among genes, variants, traits, drugs, environments, anatomical structures and diseases implicitly found through gene set intersections. By enumerating the common and distinct biological molecules associated with all subsets of curated or user submitted groups of gene sets and gene networks, GeneWeaver empowers users with the ability to construct data driven descriptions of shared and unique biological processes, diseases and traits within and across species.
LncBook is a curated knowledgebase of human lncRNAs that features a comprehensive collection of human lncRNAs and systematic curation of lncRNAs by multi-omics data integration, functional annotation and disease association. It integrates multi-omics data from expression, methylation, genome variation and lncRNA-miRNA interaction. A core component of LncBook is the community-curated LncRNAWiki portal, which a wiki-based, publicly editable and open-content platform for community curation of human long non-coding RNAs (lncRNAs).
DISNOR is a resource that uses a comprehensive collection of disease associated genes, as annotated in DisGeNET, to interrogate SIGNOR (https://signor.uniroma2.it) in order to assemble disease-specific logic networks linking disease associated genes by causal relationships. DISNOR is an open resource where more than 4000 disease-networks, linking ~ 2800 disease genes, can be explored. For each disease curated in DisGeNET, DISNOR links disease genes through manually annotated causal relationships and the inferred 'patho-pathways' can be visualised at different level of complexity.
Mitochondrial Disease Sequence Data Resource
The Mitochondrial Disease Sequence Data Resource (MSeqDR) is a centralized genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. It integrates community knowledge from expert‐curated databases with genomic and phenotype data shared by clinicians and researchers.
Scroll for more...
This record is not implemented by any policy.
This record is in need of a maintainer. If you login, you'll be able to claim this record.
U.S. National Library of Medicine (Government body)