Improved performance in protein secondary structure prediction by combining multiple predictions |
| |
Authors: | Huang De-Shuang Huang Xin |
| |
Institution: | Intelligent Computing Lab., Hefei Institute of Intelligent Machines, CAS, P.O. Box 1130, Hefei, Anhui, China. dshuang@iim.ac.cn |
| |
Abstract: | In this paper(1) we present a novel framework for protein secondary structure prediction. In this prediction framework, firstly we propose a novel parameterized semi-probability profile, which combines single sequence with evolutionary information effectively. Secondly, different semi-probability profiles are respectively applied as network input to predict protein secondary structure. Then a comparison among these different predictions is discussed in this article. Finally, na?ve Bayes approaches are used to combine these predictions in order to obtain a better prediction performance than individual prediction. The experimental results show that our proposed framework can indeed improve the prediction accuracy. |
| |
Keywords: | |
本文献已被 PubMed 等数据库收录! |
|