Information processing and living systems /

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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 p...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Bajić, V. B. (Vladimir B.), Tan, Tin Wee
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Singapore ; Hackensack, NJ : Imperial College Press ; Distributed by World Scientific Pub., ©2005.
Colección:Series on advances in bioinformatics and computational biology ; v. 2.
Temas:
Bioinformatics.
Information modeling.
Natural computation.
Biology > Data processing.
Human information processing.
Computational biology.
Computational Biology
Mental Processes
Bio-informatique.
Modèles d'information.
Calcul naturel.
Biologie > Informatique.
Traitement de l'information chez l'être humain.
NATURE > Reference.
SCIENCE > Life Sciences > General.
SCIENCE > Life Sciences > Biology.
Computational biology
Bioinformatics
Natural computation
Biology > Data processing
Human information processing
Information modeling
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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.

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