Network analysis of differential expression for the identification of disease-causing genes.

ABSTRACT: Genetic studies (in particular linkage and association studies) identify chromosomal regions involved in a disease or phenotype of interest, but those regions often contain many candidate genes, only a few of which can be followed-up for biological validation. Recently, computational methods to identify (prioritize) the most promising candidates within a region have been proposed, but they are usually not applicable to cases where little is known about the phenotype (no or few confirmed disease genes, fragmentary understanding of the biological cascades involved). We seek to overcome this limitation by replacing knowledge about the biological process by experimental data on differential gene expression between affected and healthy individuals. Considering the problem from the perspective o

SUBMITTER: Nitsch D 

PROVIDER: S-EPMC2677677 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature