计算机科学
领域(数学)
序列(生物学)
软件
贝叶斯概率
数据科学
理论计算机科学
数学证明
数据挖掘
人工智能
生物
数学
程序设计语言
遗传学
几何学
纯数学
出处
期刊:Oxford University Press eBooks
[Oxford University Press]
日期:2006-10-05
被引量:786
标识
DOI:10.1093/acprof:oso/9780198567028.001.0001
摘要
Abstract The field of molecular evolution has experienced explosive growth in recent years due to the rapid accumulation of genetic sequence data, continuous improvements to computer hardware and software, and the development of sophisticated analytical methods. The increasing availability of large genomic data sets requires powerful statistical methods to analyse and interpret them, generating both computational and conceptual challenges for the field. This book provides a comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics. It describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to furthering our understanding of the evolution of genes and genomes. The book emphasizes essential concepts rather than mathematical proofs. It includes detailed derivations and implementation details, as well as numerous illustrations, worked examples, and exercises.
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