Genetic algorithms in molecular recognition and design
Trends in biotechnologyPublished 1 December 1995
Peter Willett
Citations114
SJR quartileQ1
SJR score2.36
SNIP2.27
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TL;DR
A genetic algorithm takes an initial set of possible starting solutions, and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution.
Abstract
Genetic algorithms provide a novel tool for the investigation of combinatorial optimization problems. A genetic algorithm takes an initial set of possible starting solutions, and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution. This approach is illustrated by reference to applications in molecular modelling, the docking of flexible ligands into protein active sites and de novo ligand design.
Keywords
Computer ScienceMedicineBiochemistry, Genetics and Molecular Biology
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