Titlebook: Computational Neurogenetic Modeling; Lubica Benuskova,Nikola Kasabov Book 2007 Springer-Verlag US 2007 Benuskova.Biomedical.Computational.

枯燥

flutter

小官

滑稽

Dawnie Andrak,Danielle Jacques,Annika Webere set of features (e.g. genes, brain signals) in a computational model. Evolutionary computation (EC) methods adopt principles from the evolution in Nature (Darwin 1859). EC methods are used in Chaps. 7 and 8 of the book to optimize gene interaction networks as part of a CNGM.

Ergots

archaeology

FATAL

https://doi.org/10.1007/978-3-030-13758-8represent knowledge about the basic mechanisms of cellular and molecular memory storage. Then we need to enhance these rules with connections to gene/protein regulatory network (GPRN) of genes and proteins that are relevant to learning and memory. Finally, a provisional CNGM of learning and memory w

crockery

Evolve

FAWN

https://doi.org/10.1007/978-1-4613-9302-3ematical and information sciences (e.g. computational intelligence — CI), neurosciences, and genetics. The chapter also discusses what methods can be used for CNGM and how. The concepts and principles introduced in this chapter are presented in detail and illustrated in the rest of the book.