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BioMed Research International
Volume 2013 (2013), Article ID 686090, 11 pages
Research Article

An Approach for Identifying Cytokines Based on a Novel Ensemble Classifier

1School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China
2Center for Cloud Computing and Big Data, Xiamen University, Xiamen, Fujian, China
3Shanghai Key Laboratory of Intelligent Information Processing, Shanghai, China
4School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China

Received 12 May 2013; Revised 2 July 2013; Accepted 15 July 2013

Academic Editor: Lei Chen

Copyright © 2013 Quan Zou 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

The supplementary material contains three files. The first file (4151.fasta) is the candidate sequences which were predicted by our method from UniProt. It contains 4151 sequences. The second file (16245.fasta) is all the cytokine sequences which is collected by us. The third file (blast.xlsx) is the blast result. 4151.fasta is chosen as the query file, and 16245.fasta is chosen as the database file. The blast.xlsx showed the similarity between the candidates predicted by our method and the known cytokines.

  1. Supplementary Material