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
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