Genetic association database

By N. Campbell. Nature reviews genetics, 2004

610 citations recorded by the source corpus.

Subfields: Epidemiology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/54a54371577545b529a8ab53b421d14a58b33ba6

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Citations in the corpus

Associating Genes and Protein Complexes with Disease via Network Propagation (2010, methodology): “We checked whether our predicted genes were already found to be involved with their query disease by searching online databases [14–16] and scientific publications.”
NONCODEV5: a comprehensive annotation database for long non-coding RNAs (2017, background): “LincSNP 2.0 is a database that links disease-associated SNPs to human large intergenic non-coding RNAs and has summarized 809 451 lncRNA SNPs from eight databases (dbGaP (42), GAD (43), GWAS Central (44), Johnson and O’Donnell (45), the NHGRI GWAS Catalog (46), PharmGKb (47), GWASdb (48) and GRASP (”
The Human Gene Mutation Database: 2008 update (2009, neutral): “Several other databases [17-19] have attempted to collate known polymorphism-disease associations but have met with only partial success owing to an over-reliance on computerized search procedures and automated data collection.”
Disease candidate gene identification and prioritization using protein interaction networks (2009, methodology): “Briefly, 19 diseases from OMIM [57] and GAD [58] were used as training sets.”
Computational tools for prioritizing candidate genes: boosting disease gene discovery (2012, background): “The Genetic Association Database (GAD) focuses on association studies of complex disorders 49 and can therefore be used to identify causative variants.”
The UCSC Genome Browser (2003, neutral): “The GAD View track shows data from the Genetic Association Database (GAD; Becker et al., 2004), an archive of human genetic association studies of complex diseases and disorders that allows the rapid identification of medically relevant polymorphism from the large volume of polymorphism and…”
The Comparative Toxicogenomics Database: update 2011 (2010, background): “The value and utility of CTD is evidenced by it being indexed at numerous other databases, including PubChem (6), PharmGKB (7), UniProt (8), T3DB (9), GAD (10) and ChemID (11), and by the inclusion of CTD’s curated information in other database products, such as STITCH (12), ToppGene (13), PhenoHM (”
DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants (2016, methodology): “The Genetic Association Database (GAD), an archive of genetic association studies (10) Additionally, DisGeNET includes two data sets obtained using different text-mining approaches -”
Network-Based Elucidation of Human Disease Similarities Reveals Common Functional Modules Enriched for Pluripotent Drug Targets (2010, methodology): “Next, we extracted genes that are significantly associated with diseases in Genetic Association Database (GAD) [42].”
Inductive matrix completion for predicting gene–disease associations (2014, background): “Similarly, the type of evidence available for genes varies—for example, specific microarray probes convey information only for certain sets of genes.”
Protein Networks as Logic Functions in Development and Cancer (2011, background): “. Cancer-associated genes (including breast and brain cancer genes) were from the Genetic Association Database”
The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins (2016, background): “GAD High Level Gene-Disease Associations (61) GWASdb SNP-Disease Associations (62)”
PATRIC: the Comprehensive Bacterial Bioinformatics Resource with a Focus on Human Pathogenic Species (2011, methodology): “Integrating data from the Genetic Association Database (8, 57), the “Genetic Association Source” table lists human genes that have been shown to have some genetic association with a bacterial disease.”