Title :
Multiple sequence alignment using evolutionary programming
Author :
Chellapilla, Kumar ; Fogel, Gary B.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA
Abstract :
Multiple sequence alignment can be used as a tool for the identification of common structure in an ordered string of nucleotides (in DNA or RNA) or amino acids (in proteins). Current multiple sequence alignment algorithms work well for sequences with high similarity but do not scale well when either the length or number of the sequences is large or if the similarity is low. The focus of the paper is to develop an evolutionary programming (EP) algorithm for multiple sequence alignment. An EP method with representation specific variation operators is proposed and tested on several data sets. Comparisons to other algorithms suggests that this algorithm is well suited to the multiple sequence alignment problem
Keywords :
biology computing; data handling; evolutionary computation; molecular biophysics; proteins; sequences; DNA; EP algorithm; EP method; RNA; amino acids; common structure; data sets; evolutionary programming; multiple sequence alignment algorithms; multiple sequence alignment problem; nucleotides; ordered string; proteins; representation specific variation operators; Amino acids; DNA; Evolution (biology); Genetic programming; Organisms; Phylogeny; Proteins; RNA; Sequences; Testing;
Conference_Titel :
Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5536-9
DOI :
10.1109/CEC.1999.781958