Independent component analysis in non-hypothesis driven metabolomics: Improvement of pattern discovery and simplification of biological data interpretation demonstrated with plasma samples of exercising humans

	Independent component analysis in non-hypothesis driven metabolomics: Improvement of pattern discovery and simplification of biological data interpretation demonstrated with plasma samples of exercising humans
	Li, Xiang 1,6; Hansen, Jakob 2,3; Zhao, Xinjie 1; Lu, Xin 1; Weigert, Cora 4,5; Haering, Hans-Ulrich 4,5; Pedersen, Bente K.2,3; Plomgaard, Peter 2,3; Lehmann, Rainer 4,5; Xu, Guowang 1
刊名	journal of chromatography b-analytical technologies in the biomedical and life sciences
	2012-12-01
卷号	910 页码:156-162
关键词	Independent component analysis Metabolomics Exercise Metabolic profiling GC-MS
通讯作者	rainerlehmann ; 许国旺
产权排序	1,1
英文摘要	in a non-hypothesis driven metabolomics approach plasma samples collected at six different time points (before, during and after an exercise bout) were analyzed by gas chromatography-time of flight mass spectrometry (gc-tof ms). since independent component analysis (ica) does not need a priori information on the investigated process and moreover can separate statistically independent source signals with non-gaussian distribution, we aimed to elucidate the analytical power of ica for the metabolic pattern analysis and the identification of key metabolites in this exercise study. a novel approach based on descriptive statistics was established to optimize ica model. in the gc-tof ms data set the number of principal components after whitening and the number of independent components of ica were optimized and systematically selected by descriptive statistics. the elucidated dominating independent components were involved in fuel metabolism, representing one of the most affected metabolic changes occurring in exercising humans. conclusive time dependent physiological changes of the metabolic pattern under exercise conditions were detected. we conclude that after optimization ica can successfully elucidate key metabolite pattern as well as characteristic metabolites in metabolic processes thereby simplifying the explanation of complex biological processes. moreover. ica is capable to study time series in complex experiments with multi-levels and multi-factors. (c) 2012 elsevier b.v. all rights reserved.
学科主题	物理化学
WOS标题词	science & technology ; life sciences & biomedicine ; physical sciences
类目[WOS]	biochemical research methods ; chemistry, analytical
研究领域[WOS]	biochemistry & molecular biology ; chemistry
关键词[WOS]	arabidopsis-thaliana ; classification ; chemometrics ; algorithms ; separation ; profiles
收录类别	SCI
语种	英语
WOS记录号	WOS:000312174700018
公开日期	2013-10-11
内容类型	期刊论文
源URL	[http://159.226.238.44/handle/321008/118215]
专题	大连化学物理研究所_中国科学院大连化学物理研究所
作者单位	1.Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian 16023, Peoples R China 2.Univ Copenhagen, Fac Hlth Sci, Rigshosp, Dept Infect Dis,Ctr Inflammat & Metab, DK-2100 Copenhagen, Denmark 3.Univ Copenhagen, Fac Hlth Sci, Rigshosp, Copenhagen Muscle Res Ctr, DK-2100 Copenhagen, Denmark 4.Univ Tubingen Hosp, Div Clin Chem & Pathobiochem, Cent Lab, D-72076 Tubingen, Germany 5.Univ Tubingen, Paul Langerhans Inst Tubingen, Helmholtz Ctr Munich, Inst Diabet Res & Metab Dis, D-72076 Tubingen, Germany 6.Qinhuangdao Entry Exit Inspect & Quarantine Bur P, Qinhuangdao 066004, Peoples R China
推荐引用方式 GB/T 7714	Li, Xiang,Hansen, Jakob,Zhao, Xinjie,et al. Independent component analysis in non-hypothesis driven metabolomics: Improvement of pattern discovery and simplification of biological data interpretation demonstrated with plasma samples of exercising humans[J]. journal of chromatography b-analytical technologies in the biomedical and life sciences,2012,910:156-162.
APA	Li, Xiang.,Hansen, Jakob.,Zhao, Xinjie.,Lu, Xin.,Weigert, Cora.,...&Xu, Guowang.(2012).Independent component analysis in non-hypothesis driven metabolomics: Improvement of pattern discovery and simplification of biological data interpretation demonstrated with plasma samples of exercising humans.journal of chromatography b-analytical technologies in the biomedical and life sciences,910,156-162.
MLA	Li, Xiang,et al."Independent component analysis in non-hypothesis driven metabolomics: Improvement of pattern discovery and simplification of biological data interpretation demonstrated with plasma samples of exercising humans".journal of chromatography b-analytical technologies in the biomedical and life sciences 910(2012):156-162.