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Artificial Intelligence and Molecular Biology

Artificial Intelligence and Molecular Biology

Lawrence Hunter
3.5/5 ( ratings)
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.

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.
Language
English
Pages
470
Format
Paperback
Publisher
AAAI Press
Release
March 18, 1993
ISBN
0262581159
ISBN 13
9780262581158

Artificial Intelligence and Molecular Biology

Lawrence Hunter
3.5/5 ( ratings)
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.

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.
Language
English
Pages
470
Format
Paperback
Publisher
AAAI Press
Release
March 18, 1993
ISBN
0262581159
ISBN 13
9780262581158

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