Literature DB >> 8346439

Genetic algorithms: principles of natural selection applied to computation.

S Forrest1.   

Abstract

A genetic algorithm is a form of evolution that occurs on a computer. Genetic algorithms are a search method that can be used for both solving problems and modeling evolutionary systems. With various mapping techniques and an appropriate measure of fitness, a genetic algorithm can be tailored to evolve a solution for many types of problems, including optimization of a function of determination of the proper order of a sequence. Mathematical analysis has begun to explain how genetic algorithms work and how best to use them. Recently, genetic algorithms have been used to model several natural evolutionary systems, including immune systems.

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Year:  1993        PMID: 8346439     DOI: 10.1126/science.8346439

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  59 in total

1.  Emergence of homeostasis and "noise imprinting" in an evolution model.

Authors:  M D Stern
Journal:  Proc Natl Acad Sci U S A       Date:  1999-09-14       Impact factor: 11.205

2.  A genetic algorithm for the automated generation of small organic molecules: drug design using an evolutionary algorithm.

Authors:  D Douguet; E Thoreau; G Grassy
Journal:  J Comput Aided Mol Des       Date:  2000-07       Impact factor: 3.686

3.  Fast exact string pattern-matching algorithms adapted to the characteristics of the medical language.

Authors:  C Lovis; R H Baud
Journal:  J Am Med Inform Assoc       Date:  2000 Jul-Aug       Impact factor: 4.497

4.  A stochastic algorithm for global optimization and for best populations: a test case of side chains in proteins.

Authors:  Meir Glick; Anwar Rayan; Amiram Goldblum
Journal:  Proc Natl Acad Sci U S A       Date:  2002-01-15       Impact factor: 11.205

5.  Simulating self-organized molecular patterns using interaction-site models.

Authors:  M Balbás Gambra; C Rohr; K Gruber; B A Hermann; T Franosch
Journal:  Eur Phys J E Soft Matter       Date:  2012-03-30       Impact factor: 1.890

6.  An improved curvilinear gradient method for parameter optimization in complex biological models.

Authors:  David Szekely; Jamie I Vandenberg; Socrates Dokos; Adam P Hill
Journal:  Med Biol Eng Comput       Date:  2010-07-30       Impact factor: 2.602

7.  Ion accumulation in a protein nanocage: finding noisy temporal sequences using a genetic algorithm.

Authors:  Craig C Jolley; Trevor Douglas
Journal:  Biophys J       Date:  2010-11-17       Impact factor: 4.033

8.  Optimization of drug combinations using Feedback System Control.

Authors:  Patrycja Nowak-Sliwinska; Andrea Weiss; Xianting Ding; Paul J Dyson; Hubert van den Bergh; Arjan W Griffioen; Chih-Ming Ho
Journal:  Nat Protoc       Date:  2016-01-14       Impact factor: 13.491

9.  Utilizing high throughput screening data for predictive toxicology models: protocols and application to MLSCN assays.

Authors:  Rajarshi Guha; Stephan C Schürer
Journal:  J Comput Aided Mol Des       Date:  2008-02-19       Impact factor: 3.686

10.  A genetic algorithm for variable selection in logistic regression analysis of radiotherapy treatment outcomes.

Authors:  Olivier Gayou; Shiva K Das; Su-Min Zhou; Lawrence B Marks; David S Parda; Moyed Miften
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

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