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MicroRNA Set : A Novel Way to Uncover the Potential Black Box of Chronic Heart Failure in MicroRNA Microarray Analysis

Guomin Shi1,2, Qinghua Cui3,*, and Youyi Zhang1,2,*

1Institute of Vascular Medicine, Peking University Third Hospital and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing, China 100191
2Academy for Advanced Interdisciplinary Studies, Peking University, No.5 Yiheyuan Rd Haidian District, Beijing, P.R.China 100871
3Department of Medical Informatics, Peking University Health Science Center, No.38 Xueyuan Rd, Haidian District, Beijing, P.R.China 100083
*Corresponding authors:
Dr. Youyi Zhang,
Institute of Vascular Medicine,
Peking University Third Hospital and Key Laboratory of Molecular Cardiovascular Science,
Ministry of Education, Beijing, China 100191,
E-mail : zhangyy@bjmu.edu.cn
Dr. Qinghua Cui,
Department of Medical Informatics, Peking University Health Science Center,
No.38 Xueyuan Rd, Haidian District, Beijing,
P.R.China 100083,
E-mail: cuiqinghua@bjmu.edu.cn
Qinghua Cui, Department of Medical Informatics, Peking University Health Science Center, No.38 Xueyuan Rd, Haidian District, Beijing, P.R.China 100083, E-mail: cuiqinghua@bjmu.edu.cn
Received February 24, 2009; Accepted August 15, 2009; Published August 16, 2009
Citation: Shi G, Cui Q, Zhang Y (2009) MicroRNA Set : A Novel Way to Uncover the Potential Black Box of Chronic
Heart Failure in MicroRNA Microarray Analysis. J Comput Sci Syst Biol 2: 240-246. doi:10.4172/jcsb.1000036
Copyright: © 2009 Shi G, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract

As the prime criminal among all the cardio-vascular diseases, chronic heart failure (CHF) is still far from being fully understood after decades of study by researchers. The booming bioinformatics studies, especially the microRNA (miRNA) microarray analysis, have significantly accelerated the uncovering of underlying mechanisms of human diseases. However, these miRNA researches mainly focus on single miRNA, paying less attention to the group characteristics of miRNAs, which may ignore the group characteristics of miRNAs. Here we introduce a novel miRNA set concept incorporation with a group analysis method of CHF miRNA microarray expression. Our results show great accordance with previous studies, and also reveal potential characteristics of miRNAs in CHF. Furthermore, this novel miRNA set approach may give us new insights into other diseases studies as well.

 
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