HARACNe: improving the accuracy of regulatory model reverse engineering via higher-order data processing inequality tests.

ABSTRACT: A key goal of systems biology is to elucidate molecular mechanisms associated with physiologic and pathologic phenotypes based on the systematic and genome-wide understanding of cell context-specific molecular interaction models. To this end, reverse engineering approaches have been used to systematically dissect regulatory interactions in a specific tissue, based on the availability of large molecular profile datasets, thus improving our mechanistic understanding of complex diseases, such as cancer. In this paper, we introduce high-order Algorithm for the Reconstruction of Accurate Cellular Network (hARACNe), an extension of the ARACNe algorithm for the dissection of transcriptional regulatory networks. ARACNe uses the data processing inequality (DPI), from information theory, to detect a

SUBMITTER: Jang IS 

PROVIDER: S-EPMC3915831 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature