A Parallel Genetic Algorithm for Polypeptide Three Dimensional Structure Prediction. A Transputer Implementation

1996 ◽  
Vol 36 (2) ◽  
pp. 258-269 ◽  
Author(s):  
Carlos Adriel Del Carpio
Keyword(s):  
Genetic Algorithm ◽  
Structure Prediction ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Parallel Genetic Algorithm ◽  
Three Dimensional Structure

scholarly journals RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction

RNA ◽  
2012 ◽  
Vol 18 (4) ◽  
pp. 610-625 ◽  
Author(s):  
J. A. Cruz ◽  
M.-F. Blanchet ◽  
M. Boniecki ◽  
J. M. Bujnicki ◽  
S.-J. Chen ◽  
...  
Keyword(s):  
Structure Prediction ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Three Dimensional Structure

Cloning, Sequence Analysis and Three-dimensional Structure Prediction of DNA Pol I from Thermophilic Geobacillus sp. MKK Isolated from an Iranian Hot Spring

2007 ◽  
Vol 142 (2) ◽  
pp. 200-208 ◽  
Author(s):  
Mohammad Khalaj-Kondori ◽  
Majid Sadeghizadeh ◽  
Khosro Khajeh ◽  
Hossein Naderi-Manesh ◽  
Ali Mohammad Ahadi ◽  
...  
Keyword(s):  
Sequence Analysis ◽  
Structure Prediction ◽  
Hot Spring ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Three Dimensional Structure ◽  
Pol I

scholarly journals Protein Structure Prediction Based on Improved Genetic Algorithm

2020 ◽  
Vol 11 (9) ◽  
pp. 450-454
Author(s):  
Jiaxi Liu ◽  
Keyword(s):  
Genetic Algorithm ◽  
Protein Structure ◽  
Amino Acid ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Improved Genetic Algorithm ◽  
Research Areas

The prediction of protein three-dimensional structure from amino acid sequence has been a challenge problem in bioinformatics, owing to the many potential applications for robust protein structure prediction methods. Protein structure prediction is essential to bioscience, and its research results are important for other research areas. Methods for the prediction an才d design of protein structures have advanced dramatically. The prediction of protein structure based on average hydrophobic values is discussed and an improved genetic algorithm is proposed to solve the optimization problem of hydrophobic protein structure prediction. An adjustment operator is designed with the average hydrophobic value to prevent the overlapping of amino acid positions. Finally, some numerical experiments are conducted to verify the feasibility and effectiveness of the proposed algorithm by comparing with the traditional HNN algorithm.

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