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Informatics for Metabolomics

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Translational Biomedical Informatics

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 939))

Abstract

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

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Acknowledgment

We would like to thank the Preproposal Research Fund (grant nos.PRF4/2558 and PRF-PII/59), Faculty of Science, Kasetsart University.

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Authors and Affiliations

  1. Bioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut’s University of Technology Thonburi, Bangkhuntien, Bangkok, 10150, Thailand

    Kanthida Kusonmano

  2. Department of Zoology, Faculty of Science, Kasetsart University, Bangkok, 10900, Thailand

    Wanwipa Vongsangnak & Pramote Chumnanpuen

  3. Computational Biomodelling Laboratory for Agricultural Science and Technology, Faculty of Science, Kasetsart University, Bangkok, 10900, Thailand

    Wanwipa Vongsangnak & Pramote Chumnanpuen

Authors
  1. Kanthida Kusonmano
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  2. Wanwipa Vongsangnak
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  3. Pramote Chumnanpuen
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Corresponding author

Correspondence to Pramote Chumnanpuen .

Editor information

Editors and Affiliations

  1. Center for Systems Biology, Soochow University, Jiangsu, China

    Bairong Shen

  2. School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA

    Haixu Tang

  3. Department of Biomedical Informatics, University of California San Diego, La Jolla, California, USA

    Xiaoqian Jiang

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© 2016 Springer Science+Business Media Singapore

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Kusonmano, K., Vongsangnak, W., Chumnanpuen, P. (2016). Informatics for Metabolomics. In: Shen, B., Tang, H., Jiang, X. (eds) Translational Biomedical Informatics. Advances in Experimental Medicine and Biology, vol 939. Springer, Singapore. https://doi.org/10.1007/978-981-10-1503-8_5

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