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.

Metabolomics – technology for comprehensive detection of small molecules in an organism – lags behind the other “omics” in terms of publication and dissemination of experimental data. Among the reasons for this are difficulty precisely recording information about complicated analytical experiments (metadata), existence of various databases with their own metadata descriptions, and low reusability of the published data, resulting in submitters (the researchers who generate the data) being insufficiently motivated. To tackle these issues, we developed Metabolonote, a Semantic MediaWiki-based database designed specifically for managing metabolomic metadata. We also defined a metadata and data description format, called “Togo Metabolome Data” (TogoMD), with an ID system that is required for unique access to each level of the tree-structured metadata such as study purpose, sample, analytical method, and data analysis. Separation of the management of metadata from that of data and permission to attach related information to the metadata provide advantages for submitters, readers, and database developers. The metadata are enriched with information such as links to comparable data, thereby functioning as a hub of related data resources. They also enhance not only readers’ understanding and use of data but also submitters’ motivation to publish the data. The metadata are computationally shared among other systems via APIs, which facilitate the construction of novel databases by database developers. A permission system that allows publication of immature metadata and feedback from readers also helps submitters to improve their metadata. Hence, this aspect of Metabolonote, as a metadata preparation tool, is complementary to high-quality and persistent data repositories such as MetaboLights. A total of 808 metadata for analyzed data obtained from 35 biological species are published currently. Metabolonote and related tools are available free of cost at .

Supplementary data are available at Bioinformatics online.