ISBN: 0262195097

A detailed overview of current research in kernel methods and their applications to computational biology.

1. A Primer on Molecular Biology (Alexander Zien)
2. A Primer on Kernel Methods (Jean-Philippe Vert, Koji Tsuda and Bernhard Schölkopf)
3. Support Vector Machine Applications in Computational Biology (William S. 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 J. 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 Régis 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, Michael I. Jordan and William S. Noble)
12. Protein Classification via Kernel Matrix Completion (Taishin Kin, Tsuyoshi Kato and Koji Tsuda)
13. Accurate Splice Site Detection for Caenorhabditis elegans (Gunnar Rätsch and Sören Sonnenburg)
14. Gene Expression Analysis: Joint Feature Selection and Classifier Design (Balaji Krishnapuram, Lawrence Carin and Alexander Hartemink)
15. Gene Selection for Microarray Data (Sepp Hochreiter and Klaus Obermayer)


Hardback, 416 pages, The MIT Press (August 1, 2004)