Dynamic metabolomic data analysis: a tutorial review

被引：106

作者：

Smilde, A. K. ^{[1
]}

Westerhuis, J. A. ^{[1
]}

Hoefsloot, H. C. J. ^{[1
]}

Bijlsma, S. ^{[2
]}

Rubingh, C. M. ^{[2
]}

Vis, D. J. ^{[1
]}

Jellema, R. H. ^{[2
]}

Pijl, H. ^{[3
]}

Roelfsema, F. ^{[3
]}

van der Greef, J. ^{[2
]}

机构：

[1] Univ Amsterdam, Swammerdam Inst LifeSci, NL-1018 WV Amsterdam, Netherlands

[2] TNO Qual Life, NL-3704 HE Zeist, Netherlands

[3] Leiden Univ, Med Ctr, Dept Endocrinol & Metab Dis, Leiden, Netherlands

来源：

METABOLOMICS | 2010年 / 6卷 / 01期

关键词：

Time-resolved; Dynamic systems; Multivariate modeling; Dimension reduction; Time series analysis; Basis functions; GENE-EXPRESSION; COMPONENT ANALYSIS; SYSTEMS BIOLOGY; STATISTICAL-ANALYSIS; ASCA; PLS; RESPONSES; PROFILES; PATTERNS; MEDICINE;

D O I：

10.1007/s11306-009-0191-1

中图分类号：

R5 [内科学];

学科分类号：

100201 [内科学];

摘要：

In metabolomics, time-resolved, dynamic or temporal data is more and more collected. The number of methods to analyze such data, however, is very limited and in most cases the dynamic nature of the data is not even taken into account. This paper reviews current methods in use for analyzing dynamic metabolomic data. Moreover, some methods from other fields of science that may be of use to analyze such dynamic metabolomics data are described in some detail. The methods are put in a general framework after providing a formal definition on what constitutes a 'dynamic' method. Some of the methods are illustrated with real-life metabolomics examples.

引用

页码：3 / 17

页数：15

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