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题名: Application of Fuzzy c-Means Clustering in Data Analysis of Metabolomics
作者: Li, Xiang1;  Lu, Xin1;  Tian, Jing1, 2;  Gao, Peng1;  Kong, Hongwei1;  Xu, Guowang1
通讯作者: 许国旺
刊名: ANALYTICAL CHEMISTRY
发表日期: 2009-06-01
DOI: 10.1021/ac900353t
卷: 81, 期:11, 页:4468-4475
收录类别: SCI
文章类型: Article
部门归属: 18
项目归属: 1808
产权排名: 1;1
WOS标题词: Science & Technology ;  Physical Sciences
类目[WOS]: Chemistry, Analytical
研究领域[WOS]: Chemistry
英文摘要: Fuzzy c-means (FCM) clustering is an unsupervised method derived from fuzzy logic that is suitable for solving multiclass and ambiguous clustering problems. In this study, FCM clustering is applied to cluster metabolomics data. FCM is performed directly on the data matrix to generate a membership matrix which represents the degree of association the samples have with each cluster. The method is parametrized with the number of clusters (C) and the fuzziness coefficient (m), which denotes the degree of fuzziness in the algorithm. Both have been optimized by combining FCM with partial least-squares (PLS) using the membership matrix as the Y matrix in the PLS model. The quality parameters R(2)Y and Q(2) of the PLS model have been used to monitor and optimize C and m. Data of metabolic profiles from three gene types of Escherichia coli were used to demonstrate the method above. Different multivariable analysis methods have been compared. Principal component analysis failed to model the metabolite data, while partial least-squares discriminant analysis yielded results with overfitting. On the basis of the optimized parameters, the FCM was able to reveal main phenotype changes and individual characters of three gene types of E. coli. Coupled with PLS, FCM provides a powerful research tool for metabolomics with improved visualization, accurate classification, and outlier estimation.
关键词[WOS]: 2-DIMENSIONAL GAS-CHROMATOGRAPHY ;  PARTIAL LEAST-SQUARES ;  X GC-TOFMS ;  EMISSION-TOMOGRAPHY ;  CHEMOMETRICS ;  METABONOMICS ;  PLANT ;  IDENTIFICATION ;  SPECTROSCOPY ;  COMBINATION
语种: 英语
原文出处: 查看原文
WOS记录号: WOS:000266601800041
Citation statistics: 
内容类型: 期刊论文
URI标识: http://cas-ir.dicp.ac.cn/handle/321008/102127
Appears in Collections:中国科学院大连化学物理研究所_期刊论文

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作者单位: 1.Chinese Acad Sci, Dalian Inst Chem Phys, Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China
2.Dalian Polytech Univ, Dept Modem Technol, Dalian 116034, Peoples R China

Recommended Citation:
Li, Xiang,Lu, Xin,Tian, Jing,et al. Application of Fuzzy c-Means Clustering in Data Analysis of Metabolomics[J]. ANALYTICAL CHEMISTRY,2009,81(11):4468-4475.
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