A pipeline to create predictive functional networks: application to the tumor progression of hepatocellular carcinoma.

ABSTRACT: BACKGROUND:Integrating genome-wide gene expression patient profiles with regulatory knowledge is a challenging task because of the inherent heterogeneity, noise and incompleteness of biological data. From the computational side, several solvers for logic programs are able to perform extremely well in decision problems for combinatorial search domains. The challenge then is how to process the biological knowledge in order to feed these solvers to gain insights in a biological study. It requires formalizing the biological knowledge to give a precise interpretation of this information; currently, very few pathway databases offer this possibility. RESULTS:The presented work proposes an automatic pipeline to extract automatically regulatory knowledge from pathway databases and generate novel co

SUBMITTER: Folschette M 

PROVIDER: S-EPMC6958715 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature