Modeling information flow in biological networks

Yoo Ah Kim, Jozef H. Przytycki, Stefan Wuchty, Teresa M. Przytycka

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

Large-scale molecular interaction networks are being increasingly used to provide a system level view of cellular processes. Modeling communications between nodes in such huge networks as information flows is useful for dissecting dynamical dependences between individual network components. In the information flow model, individual nodes are assumed to communicate with each other by propagating the signals through intermediate nodes in the network. In this paper, we first provide an overview of the state of the art of research in the network analysis based on information flow models. In the second part, we describe our computational method underlying our recent work on discovering dysregulated pathways in glioma. Motivated by applications to inferring information flow from genotype to phenotype in a very large human interaction network, we generalized previous approaches to compute information flows for a large number of instances and also provided a formal proof for the method.

Original languageEnglish (US)
Article number035012
JournalPhysical Biology
Volume8
Issue number3
DOIs
StatePublished - Jun 2011
Externally publishedYes

ASJC Scopus subject areas

  • Biophysics
  • Structural Biology
  • Molecular Biology
  • Cell Biology

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