Publication

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.

Brochure

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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