Efficient ensemble schemes for protein secondary structure prediction.
This paper proposes an efficient ensemble system to tackle the protein secondary structure prediction problem with neural networks as base classifiers. The experimental results show that the multi-layer system can lead to better results. When deploying more accurate classifiers, the higher accuracy of the ensemble system can be obtained.
Liu
Kun-Hong
KH
Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, P.O. Box 1130, Hefei, Anhui 230031, China.
Xia
Jun-Feng
JF
Li
Xueling
X
D019295:Computational Biology / Q000379:methods*; D016571:Neural Networks, Computer; D011487:Protein Conformation; D017510:Protein Folding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*
D011506:Proteins