Baianu, Professor I.C. (2004) ŁukasiewiczTopos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models. [Preprint]
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Abstract
A categorical and ŁukasiewiczTopos framework for Algebraic Logic models of nonlinear dynamics in complex functional systems such as Neural Networks, Cell Genome and Interactome Networks is introduced. Łukasiewicz Algebraic Logic models of both neural and genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with nstate components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'nextstate functions' is extended to a Łukasiewicz Topos with an nvalued Łukasiewicz Algebraic Logic subobject classifier description that represents nonrandom and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.
Item Type:  Preprint 

Keywords:  Łukasiewicz models of Genetic Networks; Genome and cell interactomics models in terms of categories of Łukasiewicz logic Algebras and Lukasiewicz Topos;Łukasiewicz Topos with an nvalued Łukasiewicz Algebraic Logic subobject classifier; genetic network transformations in Carcinogenesis, developmental processes and Evolution/ Evolutionary Biology; Relational Biology of Archea, yeast and higher eukaryotic organisms; nonlinear dynamics in nonrandom, hierarchic genetic networks; proteomics coupled genomes via signaling pathways;mechanisms of neoplastic transformations of cells and topological grupoid models of genetic networks in cancer cells; natural transformations of organismic structures in Molecular Biology. 
Subjects:  Computer Science > Dynamical Systems Computer Science > Complexity Theory Computer Science > Neural Nets Biology > Theoretical Biology 
ID Code:  3701 
Deposited By:  Baianu, Professor I. C. 
Deposited On:  06 Jul 2004 
Last Modified:  11 Mar 2011 08:55 
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