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The ability to simulate a biological organism by employing a computer is related to the ability of the computer to calculate the behavior of such a dynamical system, or the "computability" of the system.* However, the two questions of computability and simulation are not equivalent. Since the question of computability can be given a precise answer in terms of recursive functions, automata theory and dynamical systems, it will be appropriate to consider it first. The more elusive question of adequate simulation of biological systems by a computer will be then addressed and a possible connection between the two answers given will be considered. A conjecture is formulated that suggests the possibility of employing an algebraic-topological, "quantum" computer (Baianu, 1971b) for analogous and symbolic simulations of biological systems that may include chaotic processes that are not, in genral, either recursively or digitally computable. Depending on the biological network being modelled, such as the Human Genome/Cell Interactome or a trillion-cell Cognitive Neural Network system, the appropriate logical structure for such simulations might be either the Quantum MV-Logic (QMV) discussed in recent publications (Chiara, 2004, and references cited therein)or Lukasiewicz Logic Algebras that were shown to be isomorphic to MV-logic algebras (Georgescu et al, 2001).

Item Type:Book Chapter
Additional Information:This updated paper addresses recent developments in quantum computation models of cognitive processes in the brain as well as in genetic networks, based on QMV- Logic and Lukasiewicz Logic Algebras (LLA)on the basis of the original published section that raised the question of biomimetics, or simulation of biosystems beyond recursive computation-based modeling, by means of n-valued logic, Quantum Computation, Quantum Automata and algebraic-topological symbolic models of both neural and genetic networks with very large numbers of components and complex, hierarchically organized brain structures.
Keywords:Cognitive Neural Networks simulation by quantum computers; algebraic-topological, symbolic computation; Genetic Networks/Genome; Interactome simulations by computers; Recursive and digital computability limitations for biological and chaotic dynamics simulations;Kauffman, random networks and Boolean algebra; Lukasiewics Logic Algebra isomporphic to MV-logic algebra as model of biological system networks; Quantum MV-Logic algebras for microphysical modelling in Quantum Genetics and Enzyme Kinetics; Categories, functors, natural transformations and Topos as adequate tools for modelling hierarchical organization in biological systems and especially super-structures involved in cognitive processes supported by multi-layered neural networks.
Subjects:Biology > Theoretical Biology
ID Code:3718
Deposited By:Baianu, Professor I.C.
Deposited On:13 Jul 2004
Last Modified:11 Mar 2011 08:55

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