Structuring Biological Systems focuses on the important components of biological systems in order to develop genetic algorithms for modeling purposes. The book considers the characteristics of biological systems from the artificial intelligence point of view, examines modeling examples of complex biological systems (such as molecular level modeling, a model of renal hemodynamics, and cognitive aspects of modeling), describes the entropy-based probability distribution for modeling of environmental and biological systems, and presents a detailed analysis of modeling cancer phenomena. Structuring Biologic Systems will benefit students and researchers interested in an interdisciplinary approach to complex problems of biological systems, as well as biologists, chemists, engineers, research physicians, and computer scientists.
Table of Contents
Structure of Genetic Algorithms in Biological Systems (S.S. Iyengar, L. Prasad, and D. Morton). Computer Modeling and Artificial Intelligence: An Introductory Review (D.P.F. Möller). Modeling of Biological Systems at the Molecular Level: Electronic and Molecular Properties of Complex Molecular Systems (N.R. Kestner). A Mathematical Model of Renal Hemodynamics and Excretory Function (T.G. Coleman and J.E. Hall). Cognitive Aspects in the Modeling and Simulation of Complex Biological Systems (B.P. Bergeron and R.L. Rouse). Entropy-Based Probability Distributions for Modeling of Environmental and Biological Systems (V.P. Singh). Computer Simulation in Cancer Research (W. Düchting). Appendices. Index.