Abstract
Genetic algorithms (GA) have been widely used in quantitative structure–activity/property relationship (QSAR/QSPR) modeling in recent years and have been shown to generate accurate and robust predictions. In a GA, a population of “chromosomes” is evolved through the processes of random mutation and crossover and evaluated using a fitness function. Here, we will review the basic principles underlying GA and provide a survey of recent applications in QSAR/QSPR, bioinformatics, and in silico drug design, with particular emphasis on the use of GAs in feature selection and dimensionality reduction, model optimization, conformational search, docking, and diversity analysis.
Original language | English |
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Title of host publication | Applications of metaheuristics in process engineering |
Publisher | Springer Nature Link |
Pages | 315-324 |
Number of pages | 10 |
ISBN (Electronic) | 978-3-319-06508-3 |
ISBN (Print) | 978-3-319-06507-6 |
DOIs | |
Publication status | Published - 1 Jan 2014 |