Simultaneous learning of instantaneous and time-delayed genetic interactions using novel information theoretic scoring technique.

ABSTRACT:

Background

Understanding gene interactions is a fundamental question in systems biology. Currently, modeling of gene regulations using the Bayesian Network (BN) formalism assumes that genes interact either instantaneously or with a certain amount of time delay. However in reality, biological regulations, both instantaneous and time-delayed, occur simultaneously. A framework that can detect and model both these two types of interactions simultaneously would represent gene regulatory networks more accurately.

Results

In this paper, we introduce a framework based on the Bayesian Network (BN) formalism that can represent both instantaneous and time-delayed interactions between genes simultaneously. A novel scoring metric having firm mathematical underpinnings is also proposed th

SUBMITTER: Morshed N 

PROVIDER: S-EPMC3529704 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature