Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2014, Article ID 294279, 10 pages
http://dx.doi.org/10.1155/2014/294279
Research Article

enDNA-Prot: Identification of DNA-Binding Proteins by Applying Ensemble Learning

1School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China
2Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China
3Shanghai Key Laboratory of Intelligent Information Processing, Shanghai 518055, China
4Gordon Life Science Institute, Belmont, Massachusetts, USA
5PKU-HKUST ShenZhen-Hong Kong Institution, Shenzhen, Guangdong 518055, China
6Peking University Shenzhen Graduate School, Shenzhen, Guangdong 518055, China
7School of Engineering & Applied Science, Aston University, Birmingham B47ET, UK
8School of Information Science and Technology, Xiamen University, Xiamen, Fujian 316005, China

Received 28 February 2014; Revised 5 May 2014; Accepted 5 May 2014; Published 26 May 2014

Academic Editor: Dongchun Liang

Copyright © 2014 Ruifeng Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

Supplementary Material S1 lists all the codes and sequences for the benchmark dataset. It contains 396 proteins, classified into 146 DNA-binding proteins and 250 non DNA-binding proteins.

Supplementary Material S2 lists all the codes and sequences for the expanded benchmark dataset. It contains 2271 proteins, classified into 146 DNA-binding proteins and 2125 non DNA-binding proteins.

Supplementary Material S3 lists all the codes and sequences for the independent dataset1. It contains 182 proteins, classified into 82 DNA-binding proteins and 100 non DNA-binding proteins.

Supplementary Material S4 lists all the codes and sequences for the independent dataset2. It contains 1585 proteins, classified into 770 DNA-binding proteins and 815 non DNA-binding proteins.

  1. Supplementary Material