Biological Evolution and Statistical Physics / Edition 1

by M. Lässig, A. Valleriani

Overview

This set of lecture notes gives a first coherent account of a novel aspect of the living world that can be called biological information. The book presents both a pedagogical and state-of-the art roadmap of this rapidly evolving area and covers the whole field, from information which is encoded in the molecular genetic code to the description of large-scale evolution of complex species networks. The book will prove useful for all those who work at the interface of biology, physics and information science.

Product Details

ISBN-13:	9783540431886
Publisher:	Springer Berlin Heidelberg
Publication date:	08/05/2002
Series:	Lecture Notes in Physics , #585
Edition description:	2002
Pages:	342
Product dimensions:	6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

Molecular information and evolution.- Statistical significance and extremal ensemble of gapped local hybrid alignment.- On the design of optimization criteria for multiple sequence alignment.- Red queen dynamics and the evolution of translational redundancy and degeneracy.- A testable genotype-phenotype map: modeling evolution of RNA molecules.- Evolutionary perspectives on protein structure, stability, and functionality.- Phylogeny.- The statistical approach to molecular phylogeny: Evidence for a nonhyperthermophilic common ancestor.- Principles of cophylogenetic maps.- Accounting for phylogenetic uncertainty in comparative studies of evolution and adaptation.- The‘ shape’ of phylogenies under simple random speciation models.- The evolution of populations and species.- Fitness landscapes.- Tempo and mode in quasispecies evolution.- Multilevel processes in evolution and development: Computational models and biological insights.- Evolutionary strategies for solving optimization problems.- Review of biological ageing on the computer.- Spatio-temporal modes of speciation.- Large-scale evolution.- Food web structure and the evolution of ecological communities.- Dynamics and topology of species networks.- Modelling macroevolutionary patterns: An ecological perspective.