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

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Neuro-Information Processing in the Brain,-infonnation processing in the brain depends not only on the organization of the brain and properties of brain neural networks, but also on the properties of processing units — neurons and signal processing networks within neurons. These internal networks involved in signal processing are comprised

Felicitous

constitute

鐵砧

Evolutionary Computation for Model and Feature Optimization,e 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.

萬靈丹

Enervate

CNGM as Integration of GPRN, ANN and Evolving Processes,ctions of neural system. Properties of all cell types, including neurons, are determined by proteins they contain (Lodish et al. 2000). In tum, the types and amounts of proteins are determined by differential transcription of different genes in response to internal and external signals. Eventually,

胎兒

相容

Applications of CNGM and Future Development,he advancement of molecular research technologies more and more data and information is available about the genetic basis of neuronal functions and diseases (see Table A.l in Appendix 1). This information can be utilized to create models of brain functions and diseases that include models of gene an

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Introduction, organizational work. It provides background information on supporting organizational actors to actively design their collaborative work processes. Of main interest are individual conceptualizations of work while ensuring syntactically correct and semantically valid work models to be processed by di