An information theoretic approach to constructing robust boolean gene regulatory networks

Bane V Vasic, Vida Ravanmehr, Anantha Raman Krishnan

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

We introduce a class of finite systems models of gene regulatory networks exhibiting behavior of the cell cycle. The network is an extension of a Boolean network model. The system spontaneously cycles through a finite set of internal states, tracking the increase of an external factor such as cell mass, and also exhibits checkpoints in which errors in gene expression levels due to cellular noise are automatically corrected. We present a 7-gene network based on Projective Geometry codes, which can correct, at every given time, one gene expression error. The topology of a network is highly symmetric and requires using only simple Boolean functions that can be synthesized using genes of various organisms. The attractor structure of the Boolean network contains a single cycle attractor. It is the smallest nontrivial network with such high robustness. The methodology allows construction of artificial gene regulatory networks with the number of phases larger than in natural cell cycle.

Original languageEnglish (US)
Article number5740844
Pages (from-to)52-65
Number of pages14
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume9
Issue number1
DOIs
StatePublished - 2012

Fingerprint

Gene Regulatory Networks
Gene Regulatory Network
Boolean Networks
Genes
Cell Cycle
Gene Expression
Attractor
Gene expression
Synthetic Genes
Cycle
Boolean Model
Projective geometry
Checkpoint
Gene Networks
Cells
Boolean Functions
Network Model
Boolean functions
Noise
Finite Set

Keywords

  • Boolean networks
  • cell cycle
  • error correction
  • error correction coding
  • Gene regulatory networks

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics
  • Medicine(all)

Cite this

An information theoretic approach to constructing robust boolean gene regulatory networks. / Vasic, Bane V; Ravanmehr, Vida; Krishnan, Anantha Raman.

In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 9, No. 1, 5740844, 2012, p. 52-65.

Research output: Contribution to journalArticle

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