DocumentCode :
2075672
Title :
Protein structure prediction using hybrid AI methods
Author :
Guan, X. ; Mural, R.J. ; Uberbacher, E.C.
Author_Institution :
Div. of Eng. Phys. & Math., Oak Ridge Nat. Lab., TN, USA
fYear :
1994
fDate :
1-4 Mar 1994
Firstpage :
471
Lastpage :
473
Abstract :
Describes a new approach for predicting protein structures based on artificial intelligence methods and genetic algorithms. We combine nearest neighbor searching algorithms, neural networks, heuristic rules and genetic algorithms to form an integrated system to predict protein structures from their primary amino acid sequences. First, we describe our methods and how they are integrated, and then apply our methods to several protein sequences. The results are very close to the real structures obtained by crystallography. Parallel genetic algorithms are also implemented
Keywords :
artificial intelligence; biology computing; genetic algorithms; macromolecular configurations; physics computing; proteins; search problems; C language; artificial intelligence; computational biology; crystallography; genetic algorithms; heuristic rules; hybrid AI methods; nearest neighbor searching algorithms; neural networks; parallel algorithms; primary amino acid sequences; protein folding; protein structure prediction; searching; Amino acids; Artificial intelligence; Artificial neural networks; DNA; Genetic algorithms; Genomics; Humans; Protein engineering; Protein sequence; Spine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence for Applications, 1994., Proceedings of the Tenth Conference on
Conference_Location :
San Antonia, TX
Print_ISBN :
0-8186-5550-X
Type :
conf
DOI :
10.1109/CAIA.1994.323633
Filename :
323633
Link To Document :
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