Protein Secondary Structure Prediction: Helical transmembrane region prediction using Adaptive Neuro-Fuzzy Inference System - Couverture souple

Khatri, Indu; A. K. Sharma, Dr.

 
9783844313239: Protein Secondary Structure Prediction: Helical transmembrane region prediction using Adaptive Neuro-Fuzzy Inference System
Couverture souple
ISBN 10 : 3844313230 ISBN 13 : 9783844313239
Editeur : LAP LAMBERT Academic Publishing, 2011

Synopsis

Over last many years, various computational models have been applied for solving various biological problems. Various transmembrane region predictors have been developed for prediction of secondary structure of proteins with varying levels of accuracy. This book provides Adaptive Neuro-Fuzzy Inference System (ANFIS) based model for predicting helical transmembrane region by acquiring the structural information of target protein directly from its sequence data. Also, a Fuzzy Inference System was developed using the same test set for comparing the performance of ANFIS model. The best configuration of ANFIS model with RMSE and accuracy as 40.92% and 76.76%, respectively, seems to outperform the fuzzy model, which attained RMSE and accuracy as 54.45% and 70.37%, respectively. The success of this approach suggests that it can find potential applications in other sequence-based analysis problems. The model decsribed in this book will be useful to bioinformaticians developing new and challenging models for solving different biological problems.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Over last many years, various computational models have been applied for solving various biological problems. Various transmembrane region predictors have been developed for prediction of secondary structure of proteins with varying levels of accuracy. This book provides Adaptive Neuro-Fuzzy Inference System (ANFIS) based model for predicting helical transmembrane region by acquiring the structural information of target protein directly from its sequence data. Also, a Fuzzy Inference System was developed using the same test set for comparing the performance of ANFIS model. The best configuration of ANFIS model with RMSE and accuracy as 40.92% and 76.76%, respectively, seems to outperform the fuzzy model, which attained RMSE and accuracy as 54.45% and 70.37%, respectively. The success of this approach suggests that it can find potential applications in other sequence-based analysis problems. The model decsribed in this book will be useful to bioinformaticians developing new and challenging models for solving different biological problems.

Biographie de l'auteur

Indu Khatri, M.Sc.: Studied Bioinformatics at Banasthali University, Rajasthan, India. Dr. A. K. Sharma, PhD: Studied Computer Science at Thapar University(Thapar Institute of Engineering & Technology), Punjab, India. Senior Scientist Computer Applications in Agriculture at National Dairy Research Institute (NDRI),Karnal, (Haryana), India.

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

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2011
Langue
anglais
ISBN 10 
3844313230
ISBN 13 
9783844313239
Reliure
Broché
Nombre de pages
64
Coordonnées du fabricant
non disponible
Personne responsable
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