DocumentCode
1989048
Title
A genetic algorithm for simplifying the amino acid alphabet
Author
Palensky, Matthew ; Ali, Hesham
Author_Institution
Coll. of Inf. Sci. & Technol, Nebraska Univ., Omaha, NE, USA
fYear
2003
fDate
11-14 Aug. 2003
Firstpage
598
Lastpage
599
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.
Keywords
biology computing; genetic algorithms; genetics; molecular biophysics; proteins; amino acid alphabet; bioinformatics; computer program; genetic algorithm; predicting protein function; protein classification; protein structure; quality simplification; Algorithm design and analysis; Amino acids; Bioinformatics; Biology computing; Clustering algorithms; Educational institutions; Genetic algorithms; Information science; Partitioning algorithms; Proteins;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics Conference, 2003. CSB 2003. Proceedings of the 2003 IEEE
Print_ISBN
0-7695-2000-6
Type
conf
DOI
10.1109/CSB.2003.1227418
Filename
1227418
Link To Document