Title :
Regularity of secondary protein structures: a genetic algorithm approach
Author :
Chu, Yen-Wei ; Sun, Chuen-Tsai
Author_Institution :
Dept. of Comput. & Inf. Sci., Nat. Chiao Tung Univ, Hsinchu, Taiwan
Abstract :
Instead of putting too much focus on current approaches to protein secondary structure prediction, the authors look at the natural instincts of protein secondary structures, and propose a schema representation which are offered for identifying regular patterns among various types of secondary protein structures. The schemas employ genetic algorithms base on a steady-state strategy and two disjunctive data sets are used to verify the fitness function for our approach. In this study, 904 schemas are found, and nearly half of the said schemas reach a confidence of 70% and higher. Finally, the paper concludes with some illustrations of significant schemas produced as part of this study, with brief explanations of their significance.
Keywords :
biology computing; data mining; genetic algorithms; learning (artificial intelligence); pattern recognition; proteins; data sets; fitness function; genetic algorithm; regular pattern identification; schema representation; secondary protein structures; steady state strategy; Amino acids; Association rules; Data mining; Frequency; Genetic algorithms; Information science; Machine learning; Proteins; Steady-state; Sun;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1341956