A genetic algorithm for simplifying the amino acid alphabet

M. Palensky, H. Ali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Simplified amino acid alphabets have been successful in several areas of bioinformatics, including predicting protein structure, predicting protein function, and protein classification. Since the number of possible simplifications is large, it is not practical to search through all possible simplifications to find one suitable for a specific application. A previous study conducted by the authors indicate that algorithms with heavy reliance on randomness tend to produce poor simplifications. Genetic algorithms have been generally successful in producing quality solutions to problems with a large solution space, though their reliance on randomness makes it difficult to create quality simplifications. This study's goal is to overcome these difficulties, and create a genetic simplification algorithm. The presented results include the genetic simplification algorithm, as well as the difficulties of creating such an algorithm. The described algorithm has led to the development of a computer program that uses a genetic algorithm to produce simplified alphabets, and these outputs are listed and analyzed.

Original languageEnglish (US)
Title of host publicationProceedings of the 2003 IEEE Bioinformatics Conference, CSB 2003
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages598-599
Number of pages2
ISBN (Electronic)0769520006, 9780769520001
DOIs
StatePublished - 2003
Event2nd International IEEE Computer Society Computational Systems Bioinformatics Conference, CSB 2003 - Stanford, United States
Duration: Aug 11 2003Aug 14 2003

Publication series

NameProceedings of the 2003 IEEE Bioinformatics Conference, CSB 2003

Other

Other2nd International IEEE Computer Society Computational Systems Bioinformatics Conference, CSB 2003
CountryUnited States
CityStanford
Period8/11/038/14/03

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications

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