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

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Proceedings of the National Academy of Sciences of the United States of America. 2009 Sep 29;106(39):16829-34. doi: 10.1073/pnas.0903766106

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A state-mutating genetic algorithm to design ion-channel models. Spruston LabMenon Lab

Menon V, Spruston N, Kath WL

Note: Research in this publication was not performed at Janelia.

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Abstract

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.

PMID: 19805381 [PubMed - indexed for MEDLINE]

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

Note: Research in this publication was not performed at Janelia.

Abstract

PMID: 19805381 [PubMed - indexed for MEDLINE]

Janelia Authors