Applications of genetic algorithms in QSAR/QSPR modeling

N Sukumar, Ganesh Prabhu, Pinaki Saha

Research output: Chapter in Book/Report/Conference proceedingChapter

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 languageEnglish
Title of host publicationApplications of metaheuristics in process engineering
PublisherSpringer Nature Link
Pages315-324
Number of pages10
ISBN (Electronic)978-3-319-06508-3
ISBN (Print)978-3-319-06507-6
DOIs
Publication statusPublished - 1 Jan 2014

Fingerprint

Dive into the research topics of 'Applications of genetic algorithms in QSAR/QSPR modeling'. Together they form a unique fingerprint.

Cite this