目次

1. Introduction - Indra Neil Sarkar 2. Data Integration: An Overview - Prakash Nadkarni and Luis Marenco 3. Knowledge Representation - Mark A. Musen 4. Hypothesis Generation from Heterogenous Data Sets - Yves A. Lussier and Haiquan Li 5. Geometric Representations in Biomedical Informatics: Applications in Automated Text Analysis - Trevor Cohen and Dominic Widdows 6. Biomedical Natural Language Processing and Text Mining - Kevin B. Cohen 7. Knowledge Discovery in Biomedical Data: Theory and Methods - John H. Holmes 8. Bayesian Methods in Biomedical Data Analysis - Hsun-Hsien Chang and Gil Alterovitz 9. Learning Classifier Systems: The Rise of Genetics-Based Machine Learning in Biomedical Data Mining - Ryan J. Urbanowicz and Jason H. Moore 10. Engineering Principles in Biomedical Informatics - Riccardo Bellazzi, Matteo Gabetta, Giorgio Leonardi 11. Biomedical Informatics Methods for Personalized Medicine and Participatory Health - Fernando Martin-Sanchez, Guillermo Lopez-Campos, Kathleen Gray 12. Linking Genomic and Clinical Data for Discovery and Personalized Care - Joshua C. Denny and Hua Xu 13. Putting Theory into Practice - Indra Neil Sarkar Appendices A1: Unix Primer - Elizabeth S. Chen A2: Ruby Primer - Elizabeth S. Chen A3: Database Primer - Elizabeth S. Chen A4: Web Services - Elizabeth S. Chen