計算生物学のための代数統計学 Algebraic Statistics for Computational Biology

計算生物学のための代数統計学<br>Algebraic Statistics for Computational Biology

個数：

計算生物学のための代数統計学
Algebraic Statistics for Computational Biology

Pachter, L. (EDT)/ Sturmfels, B. (EDT)

ウェブストア価格 ¥20,166（本体¥18,333）
Cambridge University Press（2005/08発売）
外貨定価 US$ 104.00
ポイント 183pt

提携先の海外書籍取次会社に在庫がございます。通常3週間で発送いたします。
【重要ご説明事項】
1. 納期遅延や、ご入手不能となる場合が若干ございます。
2. 複数冊ご注文の場合、分割発送となる場合がございます。
3. 美品のご指定は承りかねます。

【入荷遅延について】
世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。

◆画像の表紙や帯等は実物とは異なる場合があります。

◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
また、洋書販売価格は、ご注文確定時点での日本円価格となります。
ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。

製本 Hardcover:ハードカバー版／ページ数 434 p.
言語 ENG
商品コード 9780521857000
DDC分類 570.285

基本説明

代数統計学の概要とゲノミクスへの応用、計算ゲノミクスの実用を詳述する貴重な最新技法を紹介する唯一の書籍。
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. Contents- 1. Statistics; 2. Computation; 3. Algebra; 4. Biology; 5. Parametric inference; 6. Polytope propagation on graphs; 7. Parametric sequence alignment; 8. Bounds for optimal sequence alignment; 9. Inference functions; 10. Geometry of Markov chains; 11. Equations defining hidden Markov models; 12. The EM algorithm for hidden Markov models; 13. Homology mapping with Markov random fields; 14. Mutagenetic tree models; 15. Catalog of small trees; 16. The strand symmetric model; and more.

Full 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.

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.