Protein Secondary Structure Prediction: A Feed-forward Neural Network approach - Couverture souple

Mahdi, Md. Safiur Rahman; Zunaid Haque, A.B.M.; Al Mamun, S.M.

 
9783639273663: Protein Secondary Structure Prediction: A Feed-forward Neural Network approach
Couverture souple
ISBN 10 : 3639273664 ISBN 13 : 9783639273663
Editeur : VDM Verlag Dr. Müller, 2010

Synopsis

Protein secondary structure prediction is a very hot topic in bioinformatics. Predicting protein secondary structure means to find out the portions that contain Helix and Sheet in protein sequence. There are several methods for predicting protein secondary structure. The methods like Genetic Algorithm, Hidden Markov Model and different kinds of Neural Networks are there. Genetic Algorithm mostly deals with protein tertiary structure and sequence alignment, for Hidden Markov Model the accuracy is not good and Neural Network is the most successful for predicting protein secondary structure. So, we used the method named ?Feed Forward Neural Network? and implemented it with JOONE (Java Object Oriented Neural Engine) editor. At first we have classified the 20 protein according to their structure, size and hydrophobic manner. Then we have modeled a new architecture in feed forward network and used those classified proteins as input. Our achieved accuracy of helix prediction is 71% and sheet prediction is 65%. The result shows the improvement over previous works done in this regard. We hope that our work will be a future directive in this arena.

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Présentation de l'éditeur

Protein secondary structure prediction is a very hot topic in bioinformatics. Predicting protein secondary structure means to find out the portions that contain Helix and Sheet in protein sequence. There are several methods for predicting protein secondary structure. The methods like Genetic Algorithm, Hidden Markov Model and different kinds of Neural Networks are there. Genetic Algorithm mostly deals with protein tertiary structure and sequence alignment, for Hidden Markov Model the accuracy is not good and Neural Network is the most successful for predicting protein secondary structure. So, we used the method named ?Feed Forward Neural Network? and implemented it with JOONE (Java Object Oriented Neural Engine) editor. At first we have classified the 20 protein according to their structure, size and hydrophobic manner. Then we have modeled a new architecture in feed forward network and used those classified proteins as input. Our achieved accuracy of helix prediction is 71% and sheet prediction is 65%. The result shows the improvement over previous works done in this regard. We hope that our work will be a future directive in this arena.

Biographie de l'auteur

B.Sc. in Computer Science and Information Technology (CIT), Islamic University of Technology (IUT), OIC. Mahdi, Lecturer, Dept. of CIT, IUT, OIC. Zunaid, Lecturer, Stamford University, Dept. of CSE, Master Student in Computational Algebra, The University of Western Ontario. Mamun, Master Student in Bio-informatics, University of Manitoba.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
VDM Verlag Dr. Müller
Date d'édition
2010
Langue
anglais
ISBN 10 
3639273664
ISBN 13 
9783639273663
Reliure
Broché
Nombre de pages
80
Coordonnées du fabricant
non disponible
Personne responsable
non disponible