DocumentCode :
618000
Title :
Cellular automata for modeling protein folding using the HP model
Author :
Santos, Jose ; Villot, Pablo ; Dieguez, Martin
Author_Institution :
Dept. of Comput. Sci., Univ. of A Coruna, A Coruña, Spain
fYear :
2013
fDate :
20-23 June 2013
Firstpage :
1586
Lastpage :
1593
Abstract :
We used cellular automata (CA) for the modeling of the temporal folding of proteins. Unlike the focus of the vast research already done on the direct prediction of the final folded conformations, we will model the temporal and dynamic folding process. The CA model defines how the amino acids interact through time to obtain a folded conformation. We employed the TIP model to represent the protein conformations in a lattice, we extended the classical CA models using artificial neural networks for their implementation, and we used evolutionary computing to automatically obtain the models by means of Differential Evolution. Moreover, the modeling of the folding provides the final protein conformation.
Keywords :
biology computing; cellular automata; evolutionary computation; molecular biophysics; molecular configurations; neural nets; proteins; TIP model; amino acids; artificial neural networks; cellular automata; classical CA model; differential evolution; dynamic folding process; evolutionary computing; final folded protein conformation prediction; protein folding modeling; temporal folding process; Amino acids; Artificial neural networks; Computational modeling; Lattices; Proteins; Sociology; Protein folding; cellular automata; differential evolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
Type :
conf
DOI :
10.1109/CEC.2013.6557751
Filename :
6557751
Link To Document :
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