Unravelling personalized dysfunctional gene network of complex diseases based on differential network model.

ABSTRACT: In the conventional analysis of complex diseases, the control and case samples are assumed to be of great purity. However, due to the heterogeneity of disease samples, many disease genes are even not always consistently up-/down-regulated, leading to be under-estimated. This problem will seriously influence effective personalized diagnosis or treatment. The expression variance and expression covariance can address such a problem in a network manner. But, these analyses always require multiple samples rather than one sample, which is generally not available in clinical practice for each individual. To extract the common and specific network characteristics for individual patients in this paper, a novel differential network model, e.g. personalized dysfunctional gene network, is proposed to

SUBMITTER: Yu X 

PROVIDER: S-EPMC4467679 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature