Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.
FEBS Open Bio
; 5: 251-6, 2015.
Article
em En
| MEDLINE
| ID: mdl-25870785
ABSTRACT
In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.
AD, Alzheimer disease; Co-regulation network; Disease gene mining; GGCRN, genegene co-regulation network; HPRD, Human Protein Reference Database; KEGG, Kyoto Encyclopedia of Genes and Genomes; PPI, proteinprotein interaction; Proteinprotein interaction; RWR, random walk with restart; Random walk with restart; SNP, single-nucleotide polymorphism; eQTL; eQTLs, expression quantitative trait loci
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article