Protein Secondary Structure Prediction
Helical transmembrane region prediction using Adaptive Neuro-Fuzzy Inference System
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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 configurati...
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.
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