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Discovering the secrets of DNA

Published: 01 November 1985 Publication History

Abstract

Sophisticated software tools are becoming increasingly important in helping biologists understand how nature operates. Symbolic pattern-recognition and artificial-intelligence methodologies are contributing to the development of such software.

References

[1]
James Watson's classic book, The Molecular Biology of the Gene from W. A. Benjamin (New York, 1970) is a comprehensive overview of molecular genetics.
[2]
The most comprehensive descriptions of computer programs for DNA sequence analysis may be found in special issues of the journal Nucleic Acids Research published in January 1982 (Volume 10, Number 1) and 1984 (Volume 12, Number 1) and available as collections entitled The Applicafions of Computers fo Research on Nucleic Acids from IRL Press (Oxford, England).
[3]
An excellent review of the Yanofsky work on attenuation appears in "Attenuation in the Control of Expression of Bacterial Operons," Nature, Volume 289, February 26, 1981, pages 751-758.
[4]
The original MOLGEN project is described in "The Concept and Implementation of Skeletal Plans" by Peter Friedland and Yumi Iwasaki in the Journal of Automated Reasoning, Volume 1, Number 2, 1985, pages 161-208.

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A. Gerson Greenburg

This interesting and well-written paper contains valuable information which is presented clearly and concisely. Not only is it an excellent primer of current molecular genetic thought, it also demonstrates how artificial intelligence concepts can be applied to major problems of pattern recognition. Given that mutations represent failures in translation of “codes,” it is obvious why pattern recognition techniques are helpful in solving this class of problems. The authors do a good job of interrelating the static codes (DNA) with the dynamics and functional aspects of cellular activity in easily understandable terms. The latter, with its historical perspective, is most educational because it bridges the gap between biology and computer science, allowing “discovery” in terms of model building and generation of new theory. Neophyte and experienced workers in artificial intelligence will gain valuable concepts from reading this paper.

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Published In

cover image Communications of the ACM
Communications of the ACM  Volume 28, Issue 11
Special issue: computing in the frontiers of science and engineering
Nov. 1985
129 pages
ISSN:0001-0782
EISSN:1557-7317
DOI:10.1145/4547
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 1985
Published in CACM Volume 28, Issue 11

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