Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

ABSTRACT: The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network

SUBMITTER: Gibbs DL 

PROVIDER: S-EPMC5495484 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature