
We study the evolution of large but finite asexual populations evolving in fitness landscapes in which all mutations are either neutral or strongly deleterious. We demonstrate that despite the absence of higher fitness genotypes, adaptation takes place as regions with more advantageous distributions of neutral genotypes are discovered. Since these discoveries are typically rare events, the population dynamics can be subdivided into separate epochs, with rapid transitions between them. Within one epoch, the average fitness in the population is approximately constant. The transitions between epochs, however, are generally accompanied by a significant increase in the average fitness. We verify our theoretical considerations with two analytically tractable bitstring models.
16 pages, 4 eps figures, Latex (academic press style file), submitted to the Bulletin of Mathematical Biology
FOS: Computer and information sciences, 570, Adaptation, Biological, FOS: Physical sciences, Evolution, Molecular, Mutation Rate, Spectral Radius, Neutral Network, Physics - Biological Physics, Neural and Evolutionary Computing (cs.NE), Replication Rate, Quantitative Biology - Populations and Evolution, Condensed Matter - Statistical Mechanics, Models, Genetic, Statistical Mechanics (cond-mat.stat-mech), Populations and Evolution (q-bio.PE), Computer Science - Neural and Evolutionary Computing, Nonlinear Sciences - Adaptation and Self-Organizing Systems, Adaptive Evolution, Biological Physics (physics.bio-ph), FOS: Biological sciences, Mutation, Adaptation and Self-Organizing Systems (nlin.AO)
FOS: Computer and information sciences, 570, Adaptation, Biological, FOS: Physical sciences, Evolution, Molecular, Mutation Rate, Spectral Radius, Neutral Network, Physics - Biological Physics, Neural and Evolutionary Computing (cs.NE), Replication Rate, Quantitative Biology - Populations and Evolution, Condensed Matter - Statistical Mechanics, Models, Genetic, Statistical Mechanics (cond-mat.stat-mech), Populations and Evolution (q-bio.PE), Computer Science - Neural and Evolutionary Computing, Nonlinear Sciences - Adaptation and Self-Organizing Systems, Adaptive Evolution, Biological Physics (physics.bio-ph), FOS: Biological sciences, Mutation, Adaptation and Self-Organizing Systems (nlin.AO)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 108 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
