The role of control and system theory in systems biology

P. Wellstead, Eric Bullinger, D. Kalamatianos, O. Mason, M. Verwoerd

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

The use of new technology and mathematics to study the systems of nature is one of the most significant scientific trends of the century. Driven by the need for more precise scientific understanding, advances in automated measurement are providing rich new sources of biological and physiological data. These data provide information to create mathematical models of increasing sophistication and realism-models that can emulate biological and physiological systems with sufficient accuracy to advance our understanding of living systems and disease mechanisms. New measurement and modelling methods set the stage for control and systems theory to play their rôle in seeking out the mechanisms and principles that regulate life. It is of inestimable importance for the future of control as a discipline that this rôle is performed in the correct manner. If we handle the area wisely then living systems will present a seemingly boundless range of important new problems-just as physical and engineering systems have done in previous centuries. But there is a crucial difficulty. Faced with a bewildering array of choices in an unfamiliar area, how does a researcher select a worthwhile and fruitful problem? This article is an attempt to help by offering a control-oriented guide to the labyrinthine world of biology/physiology and its control research opportunities.
Original languageEnglish
Pages (from-to)33-47
Number of pages14
JournalAnnual Reviews in Control
Volume32
Issue number1
DOIs
Publication statusPublished - Apr 2008

Keywords

  • biology
  • systems biology
  • control systems
  • systems dynamics
  • estimation
  • system identification
  • mathematical biology
  • computational physiology

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    Wellstead, P., Bullinger, E., Kalamatianos, D., Mason, O., & Verwoerd, M. (2008). The role of control and system theory in systems biology. Annual Reviews in Control, 32(1), 33-47. https://doi.org/10.1016/j.arcontrol.2008.02.001