• DocumentCode
    3560652
  • Title

    Multi-objective mixed integer strategy for the optimisation of biological networks

  • Author

    Sendin, J.O.H. ; Exler, O. ; Banga, Julio R.

  • Author_Institution
    Process Eng. Group, IIM-CSIC (Spanish Nat. Res. Council), Vigo, Spain
  • Volume
    4
  • Issue
    3
  • fYear
    2010
  • fDate
    5/1/2010 12:00:00 AM
  • Firstpage
    236
  • Lastpage
    248
  • Abstract
    In this contribution, the authors consider multi-criteria optimisation problems arising from the field of systems biology when both continuous and integer decision variables are involved. Mathematically, they are formulated as mixed-integer non-linear programming problems. The authors present a novel solution strategy based on a global optimisation approach for dealing with this class of problems. Its usefulness and capabilities are illustrated with two metabolic engineering case studies. For these problems, the authors show how the set of optimal solutions (the so-called Pareto front) is successfully and efficiently obtained, providing further insight into the systems under consideration regarding their optimal manipulation.
  • Keywords
    Pareto optimisation; biology computing; complex networks; nonlinear programming; Pareto front; biological network optimisation; continuous decision variables; global optimisation approach; integer decision variables; metabolic engineering; mixed-integer nonlinear programming; multicriteria optimisation problems; multiobjective mixed integer strategy; systems biology;
  • fLanguage
    English
  • Journal_Title
    Systems Biology, IET
  • Publisher
    iet
  • Conference_Location
    5/1/2010 12:00:00 AM
  • ISSN
    1751-8849
  • Type

    jour

  • DOI
    10.1049/iet-syb.2009.0045
  • Filename
    5470322