Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

ABSTRACT: Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been publis

SUBMITTER: Stavrakas V 

PROVIDER: S-EPMC4447287 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature