Scalar equations for synchronous Boolean networks with biological applications

Christopher Farrow, Jack Heidel, John Maloney, Jim Rogers

Research output: Contribution to journalArticle

98 Citations (Scopus)

Abstract

One way of coping with the complexity of biological systems is to use the simplest possible models which are able to reproduce at least some nontrivial features of reality. Although two value Boolean models have a long history in technology, it is perhaps a little bit surprising that they can also represent important features of living organism. In this paper, the scalar equation approach to Boolean network models is further developed and then applied to two interesting biological models. In particular, a linear reduced scalar equation is derived from a more rudimentary nonlinear scalar equation. This simpler, but higher order, two term equation gives immediate information about both cycle and transient structure of the network.

Original languageEnglish (US)
Pages (from-to)348-354
Number of pages7
JournalIEEE Transactions on Neural Networks
Volume15
Issue number2
DOIs
StatePublished - Mar 1 2004

Fingerprint

Boolean Networks
Scalar
Boolean Model
Biological Models
Biological systems
Biological Systems
Nonlinear equations
Network Model
Higher Order
Cycle
Term

Keywords

  • Boolean network
  • Nonlinear scalar equation
  • Reduced scalar equation

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Scalar equations for synchronous Boolean networks with biological applications. / Farrow, Christopher; Heidel, Jack; Maloney, John; Rogers, Jim.

In: IEEE Transactions on Neural Networks, Vol. 15, No. 2, 01.03.2004, p. 348-354.

Research output: Contribution to journalArticle

Farrow, Christopher ; Heidel, Jack ; Maloney, John ; Rogers, Jim. / Scalar equations for synchronous Boolean networks with biological applications. In: IEEE Transactions on Neural Networks. 2004 ; Vol. 15, No. 2. pp. 348-354.
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