A Knowledge Based Differential Evolution Algorithm for Protein Structure Prediction

2019 ◽  
pp. 343-359 ◽  
Author(s):  
Pedro H. Narloch ◽  
Márcio Dorn
Keyword(s):  
Protein Structure ◽  
Differential Evolution ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Differential Evolution Algorithm ◽  
Knowledge Based ◽  
Evolution Algorithm

APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction

2015 ◽  
Vol 59 ◽  
pp. 142-157 ◽  
Author(s):  
Bruno Borguesan ◽  
Mariel Barbachan e Silva ◽  
Bruno Grisci ◽  
Mario Inostroza-Ponta ◽  
Márcio Dorn
Keyword(s):  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Three Dimensional ◽  
Knowledge Based

Protein Structure Prediction

Biotechnology ◽  
2019 ◽  
pp. 156-184
Author(s):  
Hirak Jyoti Chakraborty ◽  
Aditi Gangopadhyay ◽  
Sayak Ganguli ◽  
Abhijit Datta
Keyword(s):  
Protein Structure ◽  
Ab Initio ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Future Research ◽  
Computational Techniques ◽  
Target Sequence ◽  
Knowledge Based ◽  
Research Areas ◽  
Three Phases

The great disagreement between the number of known protein sequences and the number of experimentally determined protein structures indicate an enormous necessity of rapid and accurate protein structure prediction methods. Computational techniques such as comparative modeling, threading and ab initio modelling allow swift protein structure prediction with sufficient accuracy. The three phases of computational protein structure prediction comprise: the pre-modelling analysis phase, model construction and post-modelling refinement. Protein modelling is primarily comparative or ab initio. Comparative or template-based methods such as homology and threading-based modelling require structural templates for constructing the structure of a target sequence. The ab initio is a template-free modelling approach which proceeds by satisfying various physics-based and knowledge-based parameters. The chapter will elaborate on the three phases of modelling, the programs available for performing each, issues, possible solutions and future research areas.

Protein Structure Prediction

2018 ◽  
pp. 48-79 ◽  
Author(s):  
Hirak Jyoti Chakraborty ◽  
Aditi Gangopadhyay ◽  
Sayak Ganguli ◽  
Abhijit Datta
Keyword(s):  
Protein Structure ◽  
Ab Initio ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Future Research ◽  
Computational Techniques ◽  
Target Sequence ◽  
Knowledge Based ◽  
Research Areas ◽  
Three Phases

The great disagreement between the number of known protein sequences and the number of experimentally determined protein structures indicate an enormous necessity of rapid and accurate protein structure prediction methods. Computational techniques such as comparative modeling, threading and ab initio modelling allow swift protein structure prediction with sufficient accuracy. The three phases of computational protein structure prediction comprise: the pre-modelling analysis phase, model construction and post-modelling refinement. Protein modelling is primarily comparative or ab initio. Comparative or template-based methods such as homology and threading-based modelling require structural templates for constructing the structure of a target sequence. The ab initio is a template-free modelling approach which proceeds by satisfying various physics-based and knowledge-based parameters. The chapter will elaborate on the three phases of modelling, the programs available for performing each, issues, possible solutions and future research areas.

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