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  1. Home
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  3. Algebraic Statistics for Computational Biology
  • Cited by 144
Publisher:
Cambridge University Press
Online publication date:
August 2010
Print publication year:
2005
Online ISBN:
9780511610684
DOI:
https://doi.org/10.1017/CBO9780511610684
Subjects:
Computer Science, Computational Biology and Bioinformatics, Statistical Theory and Methods, Statistics and Probability
Information

Book description

The quantitative analysis of biological sequence data is based on methods from statistics coupled with efficient algorithms from computer science. Algebra provides a framework for unifying many of the seemingly disparate techniques used by computational biologists. This book, first published in 2005, offers an introduction to this mathematical framework and describes tools from computational algebra for designing new algorithms for exact, accurate results. These algorithms can be applied to biological problems such as aligning genomes, finding genes and constructing phylogenies. The first part of this book consists of four chapters on the themes of Statistics, Computation, Algebra and Biology, offering speedy, self-contained introductions to the emerging field of algebraic statistics and its applications to genomics. In the second part, the four themes are combined and developed to tackle real problems in computational genomics. As the first book in the exciting and dynamic area, it will be welcomed as a text for self-study or for advanced undergraduate and beginning graduate courses.

Reviews

'As the first book in this exciting and dynamic area, it will be welcomed as a text for self-study or for advanced undergraduate and beginning graduate courses.'

Source: L'enseignement mathematique

'… substantial, enthusiastically presented, and confidently written …'

Source: Publication of the International Statistical Institute

'This book is of great interest to research workers, teachers and students in applied statistics, biology, medicine and genetics.'

Source: Zentralblatt MATH

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