Inference of protein-protein interaction networks from multiple heterogeneous data.

ABSTRACT: Protein-protein interaction (PPI) prediction is a central task in achieving a better understanding of cellular and intracellular processes. Because high-throughput experimental methods are both expensive and time-consuming, and are also known of suffering from the problems of incompleteness and noise, many computational methods have been developed, with varied degrees of success. However, the inference of PPI network from multiple heterogeneous data sources remains a great challenge. In this work, we developed a novel method based on approximate Bayesian computation and modified differential evolution sampling (ABC-DEP) and regularized laplacian (RL) kernel. The method enables inference of PPI networks from topological properties and multiple heterogeneous features including gene expressio

SUBMITTER: Huang L 

PROVIDER: S-EPMC4761017 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature