Artificial Intelligence and Molecular Biology

The current volume is an effort to bridge that range of exploration, from nucleotide to abstract concept, in contemporary AI/MB research. Although this book is currently out of print in hardcopy form, links to the electronic (PDF) files of the book can be accessed from the book’s contents, listed below.


Foreward / ix
Joshua Lederberg

Chapter 1
Molecular Biology for Computer Scientists / 1
Lawrence Hunter

Chapter 2
The Computational Linguistics of Biological Sequences / 47
David B. Searls

Chapter 3
Neural Networks, Adaptive Optimization, and RNA Secondary Structure Prediction / 121
Evan W. Steeg

Chapter 4
Predicting Protein Structural Features With Artificial Neural Networks / 161
Stephen R. Holbrook, Steven M. Muskal, and Sung-Hou Kim

Chapter 5
Developing Hierarchical Representations for Protein Structures: An Incremental Approach / 195
Xiru Zhang and David Waltz

Chapter 6
Integrating AI with Sequence Analysis / 210
Richard H. Lathrop, Teresa A. Webster, Randall F. Smith, Patrick H. Winston, and Temple F. Smith

Chapter 7
Planning to Learn about Protein Structure / 259
Lawrence Hunter

Chapter 8
A Qualitative Biochemistry and its Application to the Regulation of the Tryptophan Operon / 289
Peter D. Karp

Chapter 9
Identification of Qualitatively Feasible Metabolic Pathways / 325
Michael L. Mavrovouniotis

Chapter 10
Knowledge-Based Simulation of DNA Metabolism:Prediction of Action and Envisionment of Pathways / 365
Adam R. Galper, Douglas L. Brutlag and David H. Millis

Chapter 11
An AI Approach to the Interpretation of the NMR Spectra of Proteins / 396
Peter Edwards, Derek Sleeman, Gordon C. K. Roberts, and Lu Yun Lian

Chapter 12
Molecular Scene Analysis: Crystal Structure Determination Through Imagery / 433
Janice I. Glasgow, Suzanne Fortier and Frank H. Allen

Chapter 13
Afterword: The Anti-Expert System -- Thirteen Hypotheses an AI Program Should Have Seen Through / 459
Joshua Lederberg

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