A modified fuzzy co-clustering (MFCC) approach for microarray data analysis

Sheng Yao Huang, Hsing Jen Sun, Chuen Der Huang, I. Fang Chung, Chun Hung Su

研究成果: Conference contribution同行評審

4 引文 斯高帕斯(Scopus)

摘要

Biologically a gene or a sample could participate in multiple biological pathways, and only few genes are concurrently involved in a cellular process under some specific experimental conditions. Hence, identification of a subset of genes showing similar regulations under subsets of condition in microarray data has become an important research issue. Many investigators develop bi-clustering methods to attack this problem. In this study, we adopt fuzzy co-clustering concept and design a procedure to iteratively extract bi-clusters with co-expressed gene patterns (here the entire proposed process is called a modified fuzzy co-clustering (MFCC) approach). We have applied synthetic data and compared our MFCC's performance with four well-known state-of-the-art methods. Here we have not only shown that our MFCC approach can successfully extract each designed bi-clusters in the synthetic data sets, but also have demonstrated the better performance by our MFCC approach.

原文English
主出版物標題Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE
發行者Institute of Electrical and Electronics Engineers Inc.
頁面267-272
頁數6
ISBN(電子)9781479920723
DOIs
出版狀態Published - 4 9月 2014
事件2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014 - Beijing, China
持續時間: 6 7月 201411 7月 2014

出版系列

名字IEEE International Conference on Fuzzy Systems
ISSN(列印)1098-7584

Conference

Conference2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014
國家/地區China
城市Beijing
期間6/07/1411/07/14

指紋

深入研究「A modified fuzzy co-clustering (MFCC) approach for microarray data analysis」主題。共同形成了獨特的指紋。

引用此