• DocumentCode
    2917965
  • Title

    Comparison of simulated annealing and SASS for parameter estimation of biochemical networks

  • Author

    Sayol, Josep ; Nolle, Lars ; Schaefer, Gerald ; Nakashima, Tomoharu

  • Author_Institution
    Sch. of Sci. & Technol., Nottingham Trent Univ., Nottingham
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    3568
  • Lastpage
    3571
  • Abstract
    Estimating the parameters of biochemical networks from time-courses is becoming increasingly important. There have been some attempts in the past to carry out this task in an automatic way. In this research, SASS, a novel heuristic optimisation algorithm that has only one control parameter, has been used to solve this problem. While the obtained estimations are similar to those using other recent techniques, the method presented here offers a better resistance to local minima and a decrease of a 20% in average in computational cost, without the need of finding a suitable set of control parameters.
  • Keywords
    biochemistry; biology computing; parameter estimation; search problems; simulated annealing; SASS; biochemical networks; computational cost; heuristic optimisation algorithm; parameter estimation; self-adaptive step-size search; simulated annealing; Costs; Current measurement; Equations; Evolutionary computation; Kinetic theory; Parameter estimation; Particle measurements; Random number generation; Simulated annealing; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4631280
  • Filename
    4631280