Genetic association ontologies | DNA sequence databases
The availability of genetic data has increased dramatically in recent years. The greatest value of this data is its potential for personalized medicine. Many new associations are reported every day from Genome Wide Association Studies (GWAS). However, robust, reproducible associations are elusive for some complex diseases. Ontologies present a potential way to distinguish between spurious associations and those with a potential influence on the phenotype. Such an approach would be based on finding associations of the same genetic variant with closely related, but distinct, phenotypes.
A manually curated knowledgebase on polycystic ovary syndrome (PCOS). PCOS-related information available through scientific literature is cross-linked with molecular, biochemical and clinical databases. Information on associated genes, SNPs, diseases, gene ontologies and pathways along with supporting reference literature is collated and integrated in PCOSKB. PCOSKB will be useful for scientists and clinicians. The database currently holds information on 241 genes associated with PCOS.
Provides a repository of profiles diseases and genes associated with related drugs, biological phenomena and anatomy described with MeSH vocabulary. Gendoo includes more than 1700000 associations. The database allows users to visualize associations between OMIM entries and relevant MeSH terms and compare different features. Searches can be made by OMIM IDs, OMIM titles, Entrez Gene IDs, gene names or MeSH terms.
A collaborative effort aiming to provide a comprehensive and integrative annotation of the human genes in disease network context by integrating computable controlled vocabulary of the Disease Ontology, NCBI Gene Reference Into Function (GeneRIF) and molecular interaction network (MIN). DGA integrates these resources together using semantic mappings to build an integrative set of disease-to-gene and gene-to-gene relationships with excellent coverage based on current knowledge.