Artificial Intelligence and Molecular Biology
The enormous amount of data generated by the Human Genome Project and other large-scale biological research has created a rich and challenging domain for research in artificial intelligence. These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. Focusing on novel technologies and approaches, rather than on proven applications, they cover genetic sequence analysis, protein structure representation and prediction, automated data analysis aids, and simulation of biological systems. A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book.Lawrence Hunter is Director of the Machine Learning Project at the National Library of Medicine, National Institutes of Health.
About the Editor
Lawrence E. Hunter, a founder of the International Society for Computational Biology, is Director of the Computational Bioscience Program and of the Center for Computational Pharmacology at the University of Colorado School of Medicine.