Biocomputing and Emergent Computation

The Table of Contents for the book is as follows:

• Preface

• The Advantages of Evolutionary Computation

• Critical States in Cellular Automata with Local and Global Rules

• Introns in Nature and in Simulated Structure Evolution

• Adaptive Task Allocation Inspired by a Model of Division of Labor in Social Insects

• Symbiosis of Spontaneous Hypercycles through Self-Compartmentation

• An Extended Genetic Algorithm based on the Neutral Theory

• Adaptation of Evolutionary Agents in Computational Ecologies

• Modelling Self-Organization — Approaches and a Comparison with Evolutionary Methods

• Learning from Evolution to Predict Protein Structure

• Evolution of Protein Interactions

• Pseudodihedral Potential of Protein Residues and the Prediction of Folding

• Molecular Phylogenetic Trees are Inferred by Using Minimum Model-Based Complexity

• Comparative Analysis of Different Methods for the Detection of Specificity Regions in Protein Families

• From Micro-Soft to Bio-Soft: Computing With DNA

• The Complexity and Viability of DNA Computations

• Symbolic Chemical System Based on Abstract Rewriting System and Its Halting Property

• Stepwise Generation of Hamiltonian Path with Molecules

• Models of Classical and Quantum Computation in Microtubules: Implications for Consciousness

• Biocomputation and Nonlinear Dynamics in the Primitive Sensorimotor Mechanism of Euglena gracilis

• Piconewton Forces and Nanometre Steps: An Assessment of Experimental Results for Actomyosin Interaction Using Huxley Kinetics

• Attractor Network Models of Cortical Associative Memory

• Study on Synaptic Model of Temporal Pattern Stimulation

• Astrocytes and the Ontogenesis of Local Cortical Areas

• Towards Learning Retina Implants for Partial Compensation of Retinal Degenerations

• Toward The Simulation of the Embryogenesis of Caenorhadbitis elegans: Perspectives and Visualization

• Computational Study of the Chitin Secreting Gland of Riftia pachyptila