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Statistical Theory and Methods for Evolutionary Genomics$
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Xun Gu

Print publication date: 2010

Print ISBN-13: 9780199213269

Published to Oxford Scholarship Online: January 2011

DOI: 10.1093/acprof:oso/9780199213269.001.0001

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Advanced Topics in Systems Biology and Network Evolution

Advanced Topics in Systems Biology and Network Evolution

Chapter:
(p.187) 10 Advanced Topics in Systems Biology and Network Evolution
Source:
Statistical Theory and Methods for Evolutionary Genomics
Author(s):

Xun Gu

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199213269.003.0010

As evolutionary biologists have always been concerned with the genetic basis for the emergence of complex phenotypes, advances in genomics and systems biology are facilitating a paradigm shift of molecular evolutionary biology toward a better understanding of the relationship of genotypes and phenotypes. From an evolutionary perspective, the central question is whether natural selection is a necessary and/or sufficient force to explain the emergence of genomic and cellular features that underlie the building of complex organisms. Lynch has criticized the adaptive hypothesis for the origins of organismal complexity, claiming that nothing in evolution makes sense in light of population genetics that takes the effects of mutation, genetic drift, and natural selection into account. The importance of mutation types and genetic drifts on the phenotype evolution has also been emphasized by Nei and his associates. One plausible approach to resolving these fundamental issues is to model the features of biological complexity as parameters instead of emerged properties, under the principle of population genetics and molecular evolution. This chapter discusses some recent results in this trend.

Keywords:   evolutionary genomics, population genetics, molecular evolution, Lynch, adaptive hypothesis, organismal complexity, Nei

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