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 introduces this framework and describes tools for designing new algorithms for exact, accurate results. These are applied to biological problems such as aligning genomes, finding genes and constructing phylogenies. As the first book in the exciting and dynamic area, it will be welcomed as a text for self-study or for course use.…mehr
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 introduces this framework and describes tools for designing new algorithms for exact, accurate results. These are applied to biological problems such as aligning genomes, finding genes and constructing phylogenies. As the first book in the exciting and dynamic area, it will be welcomed as a text for self-study or for course use.
Lior Pachter is Associate Professor of Mathematics at the University of California, Berkeley. He received his Ph.D. in mathematics from the Massachusetts Institute of Technology in 1999. He then moved to the mathematics department at UC Berkeley where he was a postdoctoral researcher for two years, before being hired as an assistant professor. He has been awarded an NSF Career award, and has received the Sloan Fellowship for his work on molecular biology and evolution. Equally at home amongst both mathematicians and biologists, he has published over 40 research articles in areas ranging from combinatorics to gene finding, and has participated in several large genome projects.
Inhaltsangabe
Preface Part I. Introduction to the Four Themes: 1. Statistics L. Pachter and B. Sturmfels 2. Computation L. Pachter and B. Sturmfels 3. Algebra L. Pachter and B. Sturmfels 4. Biology L. Pachter and B. Sturmfels Part II. Studies on the Four Themes: 5. Parametric inference R. Mihaescu 6. Polytope propagation on graphs M. Joswig 7. Parametric sequence alignment C. Dewey and K. Woods 8. Bounds for optimal sequence alignment S. Elizalde 9. Inference functions S. Elizalde 10. Geometry of Markov chains E. Kuo 11. Equations defining hidden Markov models N. Bray and J. Morton 12. The EM algorithm for hidden Markov models I. B. Hallgrímsdóttir, A. Milowski and J. Yu 13. Homology mapping with Markov random fields A. Caspi 14. Mutagenetic tree models N. Beerenwinkel and M. Drton 15. Catalog of small trees M. Casanellas, L. Garcia and S. Sullivant 16. The strand symmetric model M. Casanellas and S. Sullivant 17. Extending statistical models from trees to splits graphs D. Bryant 18. Small trees and generalized neighbor-joining M. Contois and D. Levy 19. Tree construction using Singular Value Decomposition N. Eriksson 20. Applications of interval methods to phylogenetics R. Sainudiin and R. Yoshida 21. Analysis of point mutations in vertebrate genomes J. Al-Aidroos and S. Snir 22. Ultra-conserved elements in vertebrate genomes M. Drton, N. Eriksson and G. Leung Index.
Preface Part I. Introduction to the Four Themes: 1. Statistics L. Pachter and B. Sturmfels 2. Computation L. Pachter and B. Sturmfels 3. Algebra L. Pachter and B. Sturmfels 4. Biology L. Pachter and B. Sturmfels Part II. Studies on the Four Themes: 5. Parametric inference R. Mihaescu 6. Polytope propagation on graphs M. Joswig 7. Parametric sequence alignment C. Dewey and K. Woods 8. Bounds for optimal sequence alignment S. Elizalde 9. Inference functions S. Elizalde 10. Geometry of Markov chains E. Kuo 11. Equations defining hidden Markov models N. Bray and J. Morton 12. The EM algorithm for hidden Markov models I. B. Hallgrímsdóttir, A. Milowski and J. Yu 13. Homology mapping with Markov random fields A. Caspi 14. Mutagenetic tree models N. Beerenwinkel and M. Drton 15. Catalog of small trees M. Casanellas, L. Garcia and S. Sullivant 16. The strand symmetric model M. Casanellas and S. Sullivant 17. Extending statistical models from trees to splits graphs D. Bryant 18. Small trees and generalized neighbor-joining M. Contois and D. Levy 19. Tree construction using Singular Value Decomposition N. Eriksson 20. Applications of interval methods to phylogenetics R. Sainudiin and R. Yoshida 21. Analysis of point mutations in vertebrate genomes J. Al-Aidroos and S. Snir 22. Ultra-conserved elements in vertebrate genomes M. Drton, N. Eriksson and G. Leung Index.
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