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BioMed Research International
Volume 2016, Article ID 6598307, 11 pages
http://dx.doi.org/10.1155/2016/6598307
Research Article

Motif-Based Text Mining of Microbial Metagenome Redundancy Profiling Data for Disease Classification

1Shanghai Public Health Clinical Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
2Shanghai Center for Bioinformation Technology, Shanghai 201203, China
3Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
4Department of Medical Microbiology and Parasitology, Institutes of Medical Sciences, Shanghai Jiao Tong University School of Medicine, Shanghai 200240, China
5Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, China

Received 28 October 2015; Accepted 12 January 2016

Academic Editor: Zhenguo Zhang

Copyright © 2016 Yin Wang 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.

How to Cite this Article

Yin Wang, Rudong Li, Yuhua Zhou, et al., “Motif-Based Text Mining of Microbial Metagenome Redundancy Profiling Data for Disease Classification,” BioMed Research International, vol. 2016, Article ID 6598307, 11 pages, 2016. https://doi.org/10.1155/2016/6598307.