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Algebraic statistics for computational biology / edited by Lior Pachter, Bernd Sturmfels.

Call Number	572.8/6
Title	Algebraic statistics for computational biology / edited by Lior Pachter, Bernd Sturmfels.
Physical Description	1 online resource (xii, 420 pages) : digital, PDF file(s).
Notes	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Contents	Statistics / L. Pachter and B. Sturmfels -- Computation / L. Pachter and B. Sturmfels -- Algebra / L. Pachter and B. Sturmfels -- Biology / L. Pachter and B. Sturmfels -- Parametric inference / R. Mihaescu -- Polytope propagation on graphs / M. Joswig -- Parametric sequence alignment / C. Dewey and K. Woods -- Bounds for optimal sequence alignment / S. Elizalde and F. Lam -- Inference functions / S. Elizalde -- Geometry of Markov chains / E. Kuo -- Equations defining hidden Markov models / N. Bray and J. Morton -- The EM algorithm for hidden Markov models / I.B. Hallgrímsdóttir, R.A. Milowski and J. Yu -- Homology mapping with Markov random fields / A. Caspi -- Mutagenetic tree models / N. Beerenwinkel and M. Drton -- Catalog of small trees / M. Casanellas, L.D. Garcia and S. Sullivant -- The strand symmetric model / M. Casanellas and S. Sullivant -- Extending tree models to splits netweorks / D. Bryant -- Small trees and generalized neighbor-joining / M. Contois and D. Levy -- Tree construction using Singular Value Decomposition / N. Eriksson -- Applications of interval methods to phylogenetics / R. Sainudiin and R. Yoshida -- Analysis of point mutations in vertebrate genomes / J. Al-Aidroos and S. Snir -- Ultra-conserved elements in vertebrate and fly genomes / M. Drton, N. Eriksson and G. Leung.
Summary	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.
Added Author	Pachter, Lior, 1973- editor. Sturmfels, Bernd, 1962- editor.
Subject	BIOMETRY. ALGEBRA.
Multimedia	https://doi.org/10.1017/CBO9780511610684

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$a Statistics / L. Pachter and B. Sturmfels -- Computation / L. Pachter and B. Sturmfels -- Algebra / L. Pachter and B. Sturmfels -- Biology / L. Pachter and B. Sturmfels -- Parametric inference / R. Mihaescu -- Polytope propagation on graphs / M. Joswig -- Parametric sequence alignment / C. Dewey and K. Woods -- Bounds for optimal sequence alignment / S. Elizalde and F. Lam -- Inference functions / S. Elizalde -- Geometry of Markov chains / E. Kuo -- Equations defining hidden Markov models / N. Bray and J. Morton -- The EM algorithm for hidden Markov models / I.B. Hallgrímsdóttir, R.A. Milowski and J. Yu -- Homology mapping with Markov random fields / A. Caspi -- Mutagenetic tree models / N. Beerenwinkel and M. Drton -- Catalog of small trees / M. Casanellas, L.D. Garcia and S. Sullivant -- The strand symmetric model / M. Casanellas and S. Sullivant -- Extending tree models to splits netweorks / D. Bryant -- Small trees and generalized neighbor-joining / M. Contois and D. Levy -- Tree construction using Singular Value Decomposition / N. Eriksson -- Applications of interval methods to phylogenetics / R. Sainudiin and R. Yoshida -- Analysis of point mutations in vertebrate genomes / J. Al-Aidroos and S. Snir -- Ultra-conserved elements in vertebrate and fly genomes / M. Drton, N. Eriksson and G. Leung.

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$a 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.

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Summary	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.
Notes	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Contents	Statistics / L. Pachter and B. Sturmfels -- Computation / L. Pachter and B. Sturmfels -- Algebra / L. Pachter and B. Sturmfels -- Biology / L. Pachter and B. Sturmfels -- Parametric inference / R. Mihaescu -- Polytope propagation on graphs / M. Joswig -- Parametric sequence alignment / C. Dewey and K. Woods -- Bounds for optimal sequence alignment / S. Elizalde and F. Lam -- Inference functions / S. Elizalde -- Geometry of Markov chains / E. Kuo -- Equations defining hidden Markov models / N. Bray and J. Morton -- The EM algorithm for hidden Markov models / I.B. Hallgrímsdóttir, R.A. Milowski and J. Yu -- Homology mapping with Markov random fields / A. Caspi -- Mutagenetic tree models / N. Beerenwinkel and M. Drton -- Catalog of small trees / M. Casanellas, L.D. Garcia and S. Sullivant -- The strand symmetric model / M. Casanellas and S. Sullivant -- Extending tree models to splits netweorks / D. Bryant -- Small trees and generalized neighbor-joining / M. Contois and D. Levy -- Tree construction using Singular Value Decomposition / N. Eriksson -- Applications of interval methods to phylogenetics / R. Sainudiin and R. Yoshida -- Analysis of point mutations in vertebrate genomes / J. Al-Aidroos and S. Snir -- Ultra-conserved elements in vertebrate and fly genomes / M. Drton, N. Eriksson and G. Leung.
Subject	BIOMETRY. ALGEBRA.
Multimedia	https://doi.org/10.1017/CBO9780511610684