9 Data Integration, Metabolic Networks and Systems Biology

Annual Plant Reviews book series, Volume 43: Biology of Plant Metabolomics
Henning Redestig

Henning Redestig

RIKEN Plant Science Center, Yokohama-shi, 17-2-2 Tsurumi-ku, Suehiro-cho, 230-0045 Japan

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Jedrzej Szymanski

Jedrzej Szymanski

Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, Golm, 14476 Germany

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Masami Y. Hirai

Masami Y. Hirai

RIKEN Plant Science Center, Yokohama-shi, 17-2-2 Tsurumi-ku, Suehiro-cho, 230-0045 Japan

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Joachim Selbig

Joachim Selbig

Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, Golm, 14476 Germany

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Lothar Willmitzer

Lothar Willmitzer

Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, Golm, 14476 Germany

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Zoran Nikoloski

Zoran Nikoloski

Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, Golm, 14476 Germany

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Kazuki Saito

Kazuki Saito

RIKEN Plant Science Center, Yokohama-shi, 17-2-2 Tsurumi-ku, Suehiro-cho, 230-0045 Japan

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First published: 19 April 2018
Citations: 3
This article was originally published in 2011 in Biology of Plant Metabolomics, Volume 43 (ISBN 9781405199544) of the Annual Plant Reviews book series, this volume edited by Robert D. Hall. The article was republished in Annual Plant Reviews online in April 2018.

Abstract

As analytical techniques and data pre-processing methods continue to improve, the bottleneck of metabolomics is shifting towards later stages of data analysis and biological interpretation. High-coverage metabolomics is only possible when combining data from multiple platforms necessitating efficient methods for data integration. Metabolomic data sets with high coverage provide a unique opportunity to estimate and study metabolic networks. Once established, these networks can provide a backbone for systems biology approaches where the aim is to construct fundamental models of metabolic regulation. In this chapter, we provide an overview of status of these topics and describe current methods and tools, their drawbacks and advantages for integrative plant metabolomics.

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