Algebraic models and their use in systems biology

Reinhard Laubenbacher, Franziska Hinkelmann, David Murrugarra, Alan Veliz-Cuba

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

9 Scopus citations

Abstract

Progress in systems biology relies on the use of mathematical and statistical models for system-level studies of biological processes. Several different modeling frameworks have been used successfully, including traditional differential-equation-based models, a variety of stochastic models, agent-based models, and Boolean networks, to name some common ones. This chapter focuses on discrete models, and describes a mathematical approach to the construction and analysis of discrete models which relies on combinatorics and computational algebraic geometry. The underlying mathematical concept is that of a polynomial dynamical system over a finite field. Examples are given of the advantages of this approach, and several applications are discussed.

Original languageEnglish
Title of host publicationNatural Computing Series
Pages443-474
Number of pages32
DOIs
StatePublished - 2014

Publication series

NameNatural Computing Series
Volume48
ISSN (Print)1619-7127

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2014.

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science

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