|online documentation||https://sourceforge.net/p/diseaseontolog ...|
No XSD schemas defined
Conditions of UseApplies to: Data use
Disease Ontology: a backbone for disease semantic integration.
Schriml LM,Arze C,Nadendla S,Chang YW,Mazaitis M,Felix V,Feng G,Kibbe WA
Nucleic Acids Res 2011
From disease ontology to disease-ontology lite: statistical methods to adapt a general-purpose ontology for the test of gene-ontology associations.
Du P,Feng G,Flatow J,Song J,Holko M,Kibbe WA,Lin SM
Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data.
Kibbe WA,Arze C,Felix V,Mitraka E,Bolton E,Fu G,Mungall CJ,Binder JX,Malone J,Vasant D,Parkinson H,Schriml LM
Nucleic Acids Res 2014
No guidelines defined
Models and Formats
No identifier schema standards defined
Genetic, genomic and molecular information pertaining to the model organism Drosophila melanogaster and related sequences. This database also contains information relating to human disease models in Drosophila, the use of transgenic constructs containing sequence from other organisms in Drosophila, and information on where to buy Drosophila strains and constructs.
GWASdb comprises of collections of traits/diseases associated SNP (TASs) from current GWAS and their comprehensive functional annotations, as well as disease classifications
Stem Cell Discovery Engine
Comparison system for cancer stem cell analysis
WormBase is an international consortium of biologists and computer scientists dedicated to providing the research community with accurate, current, accessible information concerning the genetics, genomics and biology of C. elegans and related nematodes.
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.
Mouse Genome Database - a Mouse Genome Informatics (MGI) Resource
MGI is the international database resource for the laboratory mouse, providing integrated genetic, genomic, and biological data to facilitate the study of human health and disease. Data includes gene characterization, nomenclature, mapping, gene homologies among mammals, sequence links, phenotypes, allelic variants and mutants, and strain data.
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 Jackson Laboratory Clinical Knowledgebase (CKB) is a semi-automated/manually curated database of gene/variant annotations, therapy knowledge, diagnostic/prognostic information, and clinical trials related to oncology. CKB not only contains current information on the protein effect of somatic gene variants, but also connects the variant to targeted therapies through an efficacy evidence annotation. In addition, CKB captures clinical trial patient eligibility criteria that include genomic alterations (genotype-specific). The public access version of CKB encompasses 82 commonly known driver genes. Users can search CKB via gene, gene variants, drug, drug class, indication, and clinical trials. The web-based version of CKB is designed to interrogate the knowledgebase for specific data attributes while also enabling a robust browse like feature when the desired content is unknown.
DrugCentral is online drug information that provides information on active ingredients, chemical entities, pharmaceutical products, drug mode of action, indications, and pharmacologic mode of action. DrugCentral monitors FDA, EMA, and PMDA for new drug approval on regular basis to ensure currency of the resource. This resource was created and is maintained by the Division of Translational Informatics at the University of New Mexico School of Medicine.
Target Central Resource Database
TCRD is the central resource behind the Illuminating the Druggable Genome Knowledge Management Center (IDG-KMC). TCRD contains information about human targets, with special emphasis on four families of targets that are central to the NIH IDG initiative: GPCRs, kinases, ion channels and nuclear receptors. Olfactory GPCRs (oGPCRs) are treated as a separate family. A key aim of the KMC is to classify the development/druggability level of targets. The official public portal for TCRD is Pharos (pharos.nih.gov). Based on modern web design principles the Pharos interface provides facile access to all data types collected by the KMC. Given the complexity of the data surrounding any target, efficient and intuitive visualization has been a high priority, to enable users to quickly navigate & summarize search results and rapidly identify patterns. A critical feature of the interface is the ability to perform flexible search and subsequent drill down of search results. Underlying the interface is a RESTful API that provides programmatic access to all KMC data, allowing for easy consumption in user applications.
Alliance of Genome Resources
The primary mission of the Alliance of Genome Resources (the Alliance) is to develop and maintain sustainable genome information resources that facilitate the use of diverse model organisms in understanding the genetic and genomic basis of human biology, health and disease.
The Open Biological and Biomedical Ontology (OBO) Foundry is a collective of ontology developers that are committed to collaboration and adherence to shared principles. The mission of the OBO Foundry is to develop a family of interoperable ontologies that are both logically well-formed and scientifically accurate. To achieve this, OBO Foundry participants voluntarily adhere to and contribute to the development of an evolving set of principles including open use, collaborative development, non-overlapping and strictly-scoped content, and common syntax and relations, based on ontology models that work well, such as the Gene Ontology (GO). The OBO Foundry is overseen by an Operations Committee with Editorial, Technical and Outreach working groups.
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R01RR025341 (ELIXIR IIB, Italy)