A Comparative Study on Filtering Protein Secondary Structure Prediction

Authors:
Petros Kountouris;Michalis Agathocleous;Vasilis J. Promponas;Georgia Christodoulou;Simos Hadjicostas;Vassilis Vassiliades;Chris Christodoulou
Affiliations:
University of Cyprus, Nicosia;University of Cyprus, Nicosia;University of Cyprus, Nicosia;University of Cyprus, Nicosia;University of Cyprus, Nicosia;University of Cyprus, Nicosia;University of Cyprus, Nicosia
Venue:
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Year:
2012

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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.