@article {6783,
	title = {A state-mutating genetic algorithm to design ion-channel models.},
	journal = {Proceedings of the National Academy of Sciences of the United States of America},
	volume = {106},
	year = {2009},
	month = {2009 Sep 29},
	pages = {16829-34},
	abstract = {<p>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.</p>
},
	keywords = {Algorithms, Cell Membrane, Ion Channels, Models, Mutation, Neurons, Sodium Channels, Theoretical},
	issn = {1091-6490},
	doi = {10.1073/pnas.0903766106},
	author = {Menon, Vilas and Spruston, Nelson and Kath, William L}
}
