TEMPI: probabilistic modeling time-evolving differential PPI networks with multiPle information.

ABSTRACT:

Motivation

Time-evolving differential protein-protein interaction (PPI) networks are essential to understand serial activation of differentially regulated (up- or downregulated) cellular processes (DRPs) and their interplays over time. Despite developments in the network inference, current methods are still limited in identifying temporal transition of structures of PPI networks, DRPs associated with the structural transition and the interplays among the DRPs over time.

Results

Here, we present a probabilistic model for estimating Time-Evolving differential PPI networks with MultiPle Information (TEMPI). This model describes probabilistic relationships among network structures, time-course gene expression data and Gene Ontology biological processes (GOBPs). By maximizing the

SUBMITTER: Kim Y 

PROVIDER: S-EPMC4147907 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature