Algebraic Statistics for Computational Biology

Lior Pachter, Bernd Sturmfels

430 pages, parution le 30/11/2005

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Résumé

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 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.

First book in an exciting area at intersection of computation, statistics, and genomics
Has quick guides to background topics, then applies these in case studies at forefront of research
Includes links to online software and ancillary material

L'auteur - Bernd Sturmfels

Bernd Sturmfels received doctoral degrees in 1987 from the University of Washington, Seattle and TU Darmstadt, Germany. After two postdoc years at the IMA in Minneapolis and RISC-Linz in Austria, he taught at Cornell University before joining UC Berkeley in 1995, where he is now Professor of Mathematics and Computer Science. A leading experimentalist among mathematicians, Sturmfels has authored seven books and over 130 research articles in the areas of combinatorics, algebraic geometry, symbolic computation, and their applications, and he has mentored 16 doctoral students.

Sommaire

Introduction to the four themes
- Statistics
- Computation
- Algebra
- Biology
Studies on the four themes
- Parametric inference
- Polytope propagation on graphs
- Parametric sequence alignment
- Bounds for optimal sequence alignment
- Inference functions
- Geometry of Markov chains
- Equations defining hidden Markov models
- The EM algorithm for hidden Markov models
- Homology mapping with Markov random fields
- Mutagenetic tree models
- Catalog of small trees
- The strand symmetric model
- Extending tree models to splits networks
- Small trees and generalized neighbor-joining
- Tree construction using singular value decomposition
- Applications of interval methods to phylogenetics
- Analysis of point mutations in vertebrate genomes
- Ultra-conserved elements in vertebrate and fly genomes

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Cambridge University Press
Auteur(s)	Lior Pachter, Bernd Sturmfels
Parution	30/11/2005
Nb. de pages	430
Format	18 x 26
Couverture	Relié
Poids	1060g
Intérieur	Noir et Blanc
EAN13	9780521857000
ISBN13	978-0-521-85700-0