Title :
A Comparative Study on Filtering Protein Secondary Structure Prediction
Author :
Kountouris, Petros ; Agathocleous, Michalis ; Promponas, Vasilis J. ; Christodoulou, Georgia ; Hadjicostas, Simos ; Vassiliades, Vassilis ; Christodoulou, Chris
Author_Institution :
Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
Abstract :
Filtering of Protein Secondary Structure Prediction (PSSP) aims to provide physicochemically realistic results, while it usually improves the predictive performance. We performed a comparative study on this challenging problem, utilizing both machine learning techniques and empirical rules and we found that combinations of the two lead to the highest improvement.
Keywords :
bioinformatics; filtering theory; learning (artificial intelligence); molecular biophysics; molecular configurations; proteins; empirical rule; machine learning technique; protein secondary structure prediction filtering; Accuracy; Filtering; Logistics; Machine learning; Machine learning algorithms; Proteins; Training; Protein secondary structure prediction; bidirectional recurrent neural networks.; filtering; machine learning; structural bioinformatics; Animals; Artificial Intelligence; Databases, Protein; Humans; Protein Structure, Secondary; Proteins;
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
DOI :
10.1109/TCBB.2012.22
