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BioMed Research International
Volume 2014 (2014), Article ID 194812, 11 pages
Research Article

Tools and Databases of the KOMICS Web Portal for Preprocessing, Mining, and Dissemination of Metabolomics Data

1Kazusa DNA Research Institute, 2-6-7 Kazusa-kamatari, Kisarazu, Chiba 292-0818, Japan
2JST, National Bioscience Database Center (NBDC), 5-3 Yonbancho, Chiyoda-ku, Tokyo 102-0081, Japan
3Department of Nutrition and Life Science, Kanagawa Institute of Technology, 1030 Shimo-ogino, Atsugi, Kanagawa 243-0292, Japan
4Graduate School of Life and Environmental Sciences, Osaka Prefecture University, Sakai, Osaka 599-8531, Japan

Received 5 December 2013; Revised 7 February 2014; Accepted 24 February 2014; Published 9 April 2014

Academic Editor: Shigehiko Kanaya

Copyright © 2014 Nozomu Sakurai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A metabolome—the collection of comprehensive quantitative data on metabolites in an organism—has been increasingly utilized for applications such as data-intensive systems biology, disease diagnostics, biomarker discovery, and assessment of food quality. A considerable number of tools and databases have been developed to date for the analysis of data generated by various combinations of chromatography and mass spectrometry. We report here a web portal named KOMICS (The Kazusa Metabolomics Portal), where the tools and databases that we developed are available for free to academic users. KOMICS includes the tools and databases for preprocessing, mining, visualization, and publication of metabolomics data. Improvements in the annotation of unknown metabolites and dissemination of comprehensive metabolomic data are the primary aims behind the development of this portal. For this purpose, PowerGet and FragmentAlign include a manual curation function for the results of metabolite feature alignments. A metadata-specific wiki-based database, Metabolonote, functions as a hub of web resources related to the submitters' work. This feature is expected to increase citation of the submitters' work, thereby promoting data publication. As an example of the practical use of KOMICS, a workflow for a study on Jatropha curcas is presented. The tools and databases available at KOMICS should contribute to enhanced production, interpretation, and utilization of metabolomic Big Data.