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BioMed Research International
Volume 2014, Article ID 189590, 9 pages
http://dx.doi.org/10.1155/2014/189590
Research Article

Mining Seasonal Marine Microbial Pattern with Greedy Heuristic Clustering and Symmetrical Nonnegative Matrix Factorization

1College of Automation, Northwestern Polytechnical University, Xi’an 710072, China
2Key Laboratory of Information Fusion Technology, Ministry of Education, Xi’an 710072, China

Received 25 January 2014; Revised 12 March 2014; Accepted 19 March 2014; Published 27 April 2014

Academic Editor: FangXiang Wu

Copyright © 2014 Fei Liu 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.

Abstract

With the development of high-throughput and low-cost sequencing technology, a large number of marine microbial sequences were generated. The association patterns between marine microbial species and environment factors are hidden in these large amount sequences. Mining these association patterns is beneficial to exploit the marine resources. However, very few marine microbial association patterns are well investigated in this field. The present study reports the development of a novel method called HC-sNMF to detect the marine microbial association patterns. The results show that the four seasonal marine microbial association networks have characters of complex networks, the same environmental factor influences different species in the four seasons, and the correlative relationships are stronger between OTUs (taxa) than with environmental factors in the four seasons detecting community.