Kernel Methods In Computational Biology Scholkopf Bernhard Tsuda by Scho˜lkopf, Bernhard; Tsuda, Koji; Vert, Jean-philippe instant download after payment.

ix, 400 pages : 27 cm, This book provides a detailed overview of current research in kernel methods and their applications to computational biology. Following three introductory chapters -- an introduction to molecular and computational biology, a short review of kernel methods that focuses on intuitive concepts rather than technical details, and a detailed survey of recent applications of kernel methods in computational biology -- the book is divided into three sections that reflect three general trends in current research. The first part presents different ideas for the design of kernel functions specifically adapted to various biological data; the second part covers different approaches to learning from heterogeneous data; and the third part offers examples of successful applications of support vector machine methods, \"A Bradford book.\", Includes bibliographical references (pages 357-389) and index, 1. A primer on molecular biology / Alexander Zien -- 2. A primer on kernel methods / Jean-Philippe Vert, Koji Tsuda and Bernhard Scholkopf -- 3. Support vector machine applications in computational biology / William Stafford Noble -- 4. Inexact matching string kernels for protein classification / Christina Leslie, Rui Kuang and Eleazar Eskin -- 5. Fast kernels for string and tree matching / S.V.N. Vishwanathan and Alexander Johannes Smola -- 6. Local alignment kernels for biological sequences / Jean-Philippe Vert, Hiroto Saigo and Tatsuya Akutsu -- 7. Kernels for graphs / Hisashi Kashima, Koji Tsuda and Akihiro Inokuchi -- 8. Diffusion kernels / Risi Kondor and Jean-Philippe Vert -- 9. A kernel for protein secondary structure prediction / Yann Guermeur, Alain Lifchitz and Regis Vert -- 10. Heterogeneous data comparison and gene selection with kernel canonical correlation analysis / Yoshihiro Yamanishi, Jean-Philippe Vert and Minoru Kanehisa -- 11. Kernel-based integration of genomic data using semidefinite programming / Gert R.G. Lanckriet, Nello Cristianini,…