dc.contributor.author Kasabov, N
dc.contributor.author Schliebs, S
dc.contributor.author Mohemmed, A
dc.date.accessioned 2011-08-09T03:15:24Z
dc.date.available 2011-08-09T03:15:24Z
dc.date.copyright 2011-06-30
dc.date.issued 2011-08-09
dc.identifier.citation 8th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, Gargnano-Lago di Garda, Italy, 2011-06-30 - 2011-07-02
dc.identifier.uri http://hdl.handle.net/10292/1663
dc.description.abstract Computational neuro-genetic models (CNGM) combine two dynamic models – a gene regulatory network (GRN) model at a lower level, and a spiking neural network (SNN) model at a higher level to model the dynamic interaction between genes and spiking patterns of activity under certain conditions. The paper demonstrates that it is possible to model and trace over time the effect of a gene on the total spiking behavior of the SNN when the gene controls a parameter of a stochastic spiking neuron model used to build the SNN. Such CNGM can be potentially used to study neurodegenerative diseases or develop CNGM for cognitive robotics. 1
dc.publisher AUT University
dc.subject Computational neurogenetic modeling; Spiking neural networks; Gene regulatory networks; Probabilistic neural models
dc.title Modelling the effect of genes on the dynamics of probabilistic spiking neural networks for computational neurogenetic modelling
dc.type Conference Contribution
dc.rights.accessrights OpenAccess

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