A state-mutating genetic algorithm to design ion-channel models

Proc Natl Acad Sci U S A. 2009 Sep 29;106(39):16829-34. doi: 10.1073/pnas.0903766106. Epub 2009 Sep 16.


Realistic computational models of single neurons require component ion channels that reproduce experimental findings. Here, a topology-mutating genetic algorithm that searches for the best state diagram and transition-rate parameters to model macroscopic ion-channel behavior is described. Important features of the algorithm include a topology-altering strategy, automatic satisfaction of equilibrium constraints (microscopic reversibility), and multiple-protocol fitting using sequential goal programming rather than explicit weighting. Application of this genetic algorithm to design a sodium-channel model exhibiting both fast and prolonged inactivation yields a six-state model that produces realistic activity-dependent attenuation of action-potential backpropagation in current-clamp simulations of a CA1 pyramidal neuron.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms*
  • Cell Membrane / metabolism
  • Ion Channels / chemistry*
  • Ion Channels / genetics*
  • Models, Theoretical*
  • Mutation*
  • Neurons / physiology
  • Sodium Channels / chemistry
  • Sodium Channels / genetics


  • Ion Channels
  • Sodium Channels