DICP OpenIR
Application of Fuzzy c-Means Clustering in Data Analysis of Metabolomics
Li, Xiang1; Lu, Xin1; Tian, Jing1,2; Gao, Peng1; Kong, Hongwei1; Xu, Guowang1; Xu GW(许国旺)
刊名ANALYTICAL CHEMISTRY
2009-06-01
DOI10.1021/ac900353t
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
关键词[WOS]2-DIMENSIONAL GAS-CHROMATOGRAPHY ; PARTIAL LEAST-SQUARES ; X GC-TOFMS ; EMISSION-TOMOGRAPHY ; CHEMOMETRICS ; METABONOMICS ; PLANT ; IDENTIFICATION ; SPECTROSCOPY ; COMBINATION
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.
语种英语
原文出处查看原文
WOS记录号WOS:000266601800041
引用统计
被引频次:45[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://cas-ir.dicp.ac.cn/handle/321008/102127
专题中国科学院大连化学物理研究所
通讯作者Xu GW(许国旺)
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
推荐引用方式
GB/T 7714
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.
APA Li, Xiang.,Lu, Xin.,Tian, Jing.,Gao, Peng.,Kong, Hongwei.,...&许国旺.(2009).Application of Fuzzy c-Means Clustering in Data Analysis of Metabolomics.ANALYTICAL CHEMISTRY,81(11),4468-4475.
MLA Li, Xiang,et al."Application of Fuzzy c-Means Clustering in Data Analysis of Metabolomics".ANALYTICAL CHEMISTRY 81.11(2009):4468-4475.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Li, Xiang]的文章
[Lu, Xin]的文章
[Tian, Jing]的文章
百度学术
百度学术中相似的文章
[Li, Xiang]的文章
[Lu, Xin]的文章
[Tian, Jing]的文章
必应学术
必应学术中相似的文章
[Li, Xiang]的文章
[Lu, Xin]的文章
[Tian, Jing]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。