Information processing and living systems / editors, Vladimir B. Bajic, Tan Tin Wee.

Includes bibliographical references.

Print version record.

Cover -- Preface -- Overview of the Book -- Why are we putting these two domains together? -- Contents -- CHAPTER 1 A MULTI-DISCIPLINARY SURVEY OF BIOCOMPUTING: 1. MOLECULAR AND CELLULAR LEVELS* -- 1. Introduction -- 2. Lock-Key Paradigm versus Switch-Based Processing -- 3. Absolute versus Relative Determinism -- 4. Nested Hierarchy of Biocomputing Dynamics -- 5. Membrane as a Mesoscopic Substrate -- 5.1. Localized and delocalized potentials in biomembranes -- 5.2. Role of membrane fluidity in the mesoscopic dynamics -- 5.3. Electrostatic interactions as a molecular switching mechanism -- 5.4. Lateral mobility of protons on membrane surfaces: the 8220;Pacific Ocean effect -- 5.5. Role and specificity of phospholipid polar head-groups -- 5.6. Effect of transmembrane diffusion potentials and compartmentalization -- 5.7. Vesicular transport, exocytosis and synaptic transmission -- 6. Shape-Based Molecular Recognition -- 6.1. Role of short-range non-covalent bond interactions in molecular recognition -- 6.2. Molecular recognition between ferredoxin and FNR -- 6.3. Comparison of plastocyanin and cytochrome c6 -- 6.4. Molecular recognition of transducin and arrestin -- 6.5. Electronic-conformational interactions -- 7. Intracellular and Intramolecular Dynamics -- 7.1. Electrostatic interactions between a small molecule and a macromolecule -- 7.2. Effect of phosphorylation -- 7.3. Concept of intelligent materials -- 7.4. Concept of calcium-concentration microdomain -- 7.5. Errors, gradualism and evolution -- 7.6. Protein folding -- 8. Stochastic Nature of Neural Events: Controlled Randomness of Macroscopic Dynamics -- 9. Long-Term Potentiation and Synaptic Plasticity -- 10. Role of Dendrites in Information Processing -- 11. Efficiency of Biocomputing -- 12. General Discussion and Conclusion -- Acknowledgments -- References -- CHAPTER 2 A MULTI-DISCIPLINARY SURVEY OF BIOCOMPUTING: 2. SYSTEMS AND EVOLUTIONARY LEVELS, AND TECHNOLOGICAL APPLICATIONS* -- 1. Introduction -- 2. Background -- 2.1. Key conclusions of Part 1 -- 2.2. Element of non-equilibrium thermodynamics -- 2.3. Element of cellular automata -- 2.4. Element of nonlinear dynamic analysis -- 3. Biocomputing at the Evolutionary Level -- 3.1. Is evolution deterministic? -- 3.2. Explanatory power of evolution -- 3.3. Evolution as problem solving -- 3.4. Random search, exhaustive search and heuristic search -- 3.5. Enigma of homochirality of biomolecules -- 3.6. Damage control and opportunistic invention -- 3.7. Analogues and homologues -- 3.8. Co-evolution and perpetual novelty -- 3.9. Punctuated equilibrium and Cambrian explosion -- 4. Cognitive Aspects of Biocomputing -- 4.1. Models of creative problem solving -- 4.2. Parallel processing versus sequential processing in pattern recognition -- 4.3. Random search versus heuristic search -- 4.4. Dogmatism and self-imposed constraint -- 4.5. Retention phase: the need of sequential verification -- 4.6. Picture-based reasoning versus rule-based reasoning in pattern recognition -- 4.7. Advantages and disadvantages of rule-based reasoning -- 4.8. Contemporary interpretation of Freuds concept of the unconscious and Poincars introspective account -- 4.9. Interpretation of hypnagogia and serendipity -- 4.10. Gray scale of understanding and interpretation of intuition and 8220;aha experience -- 4.11. Pseudo-parallel processing -- 4.12. Need of conceptualiza.

Information processing and information flow occur in the course of an organism's development and throughout its lifespan. Organisms do not exist in isolation, but interact with each other constantly within a complex ecosystem. The relationships between organisms, such as those between prey or predator, host and parasite, and between mating partners, are complex and multidimensional. In all cases, there is constant communication and information flow at many levels. This book focuses on information processing by life forms and the use of information technology in understanding them. Readers are first given a comprehensive overview of biocomputing before navigating the complex terrain of natural processing of biological information using physiological and analogous computing models. The remainder of the book deals with "artificial" processing of biological information as a human endeavor in order to derive new knowledge and gain insight into life forms and their functioning. Specific innovative applications and tools for biological discovery are provided as the link and complement to biocomputing. Since "artificial" processing of biological information is complementary to natural processing, a better understanding of the former helps us improve the latter. Consequently, readers are exposed to both domains and, when dealing with biological problems of their interest, will be better equipped to grasp relevant ideas.

English.

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