Paper Info
Title
Protein Folding Modeling with Neural Cellular Automata Using the Face-Centered Cubic Model.
Abstract
We have modeled the protein folding process with cellular automata using the Face-Centered Cubic lattice model. An artificial neural network implements a cellular automaton-like scheme that defines the moves of each of the amino acids of the protein chain and through several time iterations until a folded protein is obtained. Differential Evolution was used to evolve these neural cellular automata, which take the information for defining the folding process from the energy space considered in the lattice model. Different proteins were used for testing the process, comparing the results of the folded structures against other methods of direct prediction of the final folded conformation.
Year
DOI
Venue
2017
10.1007/978-3-319-59740-9_13
Lecture Notes in Computer Science
Field
DocType
Volume
Cellular automaton,Protein folding,Biological system,Computer science,Differential evolution,Cubic crystal system,Artificial intelligence,Lattice model (finance),Artificial neural network,Machine learning
Conference
10337
ISSN
Citations 
PageRank 
0302-9743
1
0.36
References 
Authors
13
2
Name
Order
Citations
PageRank
Daniel Varela132.45
José Santos29714.77