کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8646190 | 1570072 | 2018 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Enhanced Artificial Neural Network for Protein Fold Recognition and Structural Class Prediction
ترجمه فارسی عنوان
شبکه عصبی مصنوعی پیشرفته برای شناخت رشته پروتئین و پیش بینی کلاس ساختاری
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کلمات کلیدی
ANNPFRSCPKNNFCSnuclear magnetic resonance - رزونانس مغناطیسی هستهایk-nearest neighbor - K نزدیکترین همسایهProtein fold recognition - تشخیص زمان پروتئینNMR - تشدید مغناطیسی هستهای Artificial Neural Network - شبکه عصبی مصنوعیSupport vector machine - ماشین بردار پشتیبانیSVM - ماشین بردار پشتیبانیProtein structure prediction - پیش بینی ساختار پروتئین
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
ژنتیک
چکیده انگلیسی
In Bioinformatics Protein Fold Recognition (PFR) and Structural Class Prediction (SCP) is a significant problem in predicting protein with a three dimensional structure. Extraction of valuable features of protein that consists of 20 amino acids to acquire more desirable classifiers is fundamental to this PFR and SCP. Feature extraction technique predominantly exploits Forward Consecutive Search Scheme (FCS) that supplements syntactical-based, evolutionary-based and physicochemical-based information. In this research work, a classifier known as Enhanced Artificial Neural Network (ANN) is employed as it is more efficient than Forward Consecutive Search scheme in order to improve the performance of PFR and SCP. The Enhanced ANN algorithm is an improved version of Artificial Neural Network when compared with various existing algorithms such as Support Vector Machine (SVM), ANN, K-Nearest Neighbor (KNN) and the Bayesian. The experiments are conducted on four datasets namely DD, EDD, TG and RDD. Ultimately, the statistical imputation of Enhanced ANN algorithm hypothesizes gives better results than other algorithms to improve the performance of PFR and SCP.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Gene Reports - Volume 12, September 2018, Pages 261-275
Journal: Gene Reports - Volume 12, September 2018, Pages 261-275
نویسندگان
P. Sudha, D. Ramyachitra, P. Manikandan,