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

Sakurai, Nozomu; Ara, Takeshi; Enomoto, Mitsuo; Motegi, Takeshi; Morishita, Yoshihiko; Kurabayashi, Atsushi; Iijima, Yoko; Ogata, Yasuhiro; Nakajima, D.; Suzuki, Hideyuki; Shibata, Daisuke

doi:10.1155/2014/194812

Cited by 43 publications

(42 citation statements)

References 63 publications

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“…Calculations of exact masses from chemical formulae were performed using the Formula Calculator tool of PowerGet 27 based on the masses of atoms and electrons published by IUPAC 28 .…”

Section: Methodsmentioning

confidence: 99%

FlavonoidSearch: A system for comprehensive flavonoid annotation by mass spectrometry

Akimoto

Ara

Nakajima

et al. 2017

Sci Rep

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Currently, in mass spectrometry-based metabolomics, limited reference mass spectra are available for flavonoid identification. In the present study, a database of probable mass fragments for 6,867 known flavonoids (FsDatabase) was manually constructed based on new structure- and fragmentation-related rules using new heuristics to overcome flavonoid complexity. We developed the FlavonoidSearch system for flavonoid annotation, which consists of the FsDatabase and a computational tool (FsTool) to automatically search the FsDatabase using the mass spectra of metabolite peaks as queries. This system showed the highest identification accuracy for the flavonoid aglycone when compared to existing tools and revealed accurate discrimination between the flavonoid aglycone and other compounds. Sixteen new flavonoids were found from parsley, and the diversity of the flavonoid aglycone among different fruits and vegetables was investigated.

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“…Calculations of exact masses from chemical formulae were performed using the Formula Calculator tool of PowerGet 27 based on the masses of atoms and electrons published by IUPAC 28 .…”

Section: Methodsmentioning

confidence: 99%

FlavonoidSearch: A system for comprehensive flavonoid annotation by mass spectrometry

Akimoto

Ara

Nakajima

et al. 2017

Sci Rep

Self Cite

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“…Alignment of the metabolite peaks is performed by PowerMatch. After the data preprocessing by PowerGet, the MS data were annotated with MF Searcher (Sakurai et al, , ). To qualify machine stability, the total number of peaks, total peak intensity, average of peak intensity, median of peak intensity, maximum value of peak intensity, and minimum value of peak intensity concerning each sample data were calculated.…”

Section: Methodsmentioning

confidence: 99%

Characterization of unique metabolites in γ‐aminobutyric acid‐rich cheese by metabolome analysis using liquid chromatography‐mass spectrometry

et al. 2019

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Fermented dairy products comprise many functional components. Our previous study using fermented milk showed that the γ‐aminobutyric acid (GABA)‐producing Lactococcus lactis 01‐7 strain can produce unique metabolites such as antihypertensive peptides, whereas this study was designed to find the unique metabolites in GABA‐rich cheese using the 01‐7 strain. Metabolites between cheese ripening with the non‐GABA‐producing L. lactis 01‐1 strain (control) and GABA‐rich cheese ripening with a mixture of 01‐1 and 01‐7 strains were compared. GABA and ornithine were detected in GABA‐rich cheese using an amino acid analyzer and citrate was detected in the control cheese using HPLC. Metabolome analysis using LC‐MS showed that peptides with unknown function and those with antihypertensive activity were higher in the GABA‐rich cheese than in the control cheese. Further analysis of the amount of the YLGY derivatives showed that the amount of YL in the GABA‐rich cheese was lower than that in the control. Practical applications Clarification of metabolites in cheese contributes to the improvement of cheese ripening, thereby providing consumers with unique cheese with good nutritional and functional characteristics. The use of the 01‐7 strain as a cheese starter might provide a functional cheese with antihypertensive‐, antioxidative‐, and anxiolytic‐like activities.

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“…Presently, Metabolonote houses 808 metadata obtained from 35 biological species. KOMICS (The Kazusa Metabolomics Portal) consists of free tools and databases for preprocessing, mining, visualization, and publication of metabolomics data , and is strengthened with additional tools, i.e. PowerGet and FragmentAlign for manual curation function for the results of metabolite feature alignments.…”

Section: Metabolomics Libraries Databases Experiments Repositories mentioning

confidence: 99%

Updates in metabolomics tools and resources: 2014–2015

2015

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acquisition. Improved machinery in metabolomics generate increasingly complex data sets which 6 create the need for more and better processing and analysis software and in-silico approaches to 7 understand the resulting data. However, a comprehensive source of information describing the 8 utility of the most recently developed and released metabolomics resources --in the form of 9 tools, software, and databases -is currently lacking. Thus, here we provide an overview of 10 freely-available, open-source, tools, algorithms and frameworks to make both upcoming and 11 established metabolomics researchers aware of the recent developments in an attempt to advance 12 and facilitate data processing workflows in their metabolomics research. The major topics 13 include tools and researches for data processing, data annotation, and data visualization in MS 14 and NMR based metabolomics. Most in this review described tools are dedicated to untargeted 15 metabolomics workflows; however, some more specialist tools are described as well. All tools 16 and resources described including their analytical and computational platform dependencies are 17 summarized in an overview Table. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 In metabolomics, data processing and interpretation represent some of the most 2 challenging and time-consuming steps in the high throughput process, regardless of the 3 analytical platform used for data generation. The exponentially growing volume of generated 4 data has triggered the research and development of tools, software, programs, databases, and 5 applications to facilitate the robust understanding of metabolic processes of biological systems. 6For instance, natural products discovery has greatly benefited from the development of open-7 access spectral and chemical databases [1]. In addition, a large number of chemoinformatics 8 tools are finding direct application in handling metabolomics data or helping in annotation. 9Targeted metabolomics investigations obtain quantitative data on a predefined set of compounds, 10while untargeted metabolomics studies provide a broader exploration of metabolites with the 11 goal of identifying new compounds [2]. Untargeted metabolomic studies are characterized by 12simultaneous qualitative and quantitative analysis of a large number of metabolites in samples. 13Currently, untargeted metabolomics is being increasingly applied in diverse areas of research however, all these applications share the same bottlenecks: i.e., the harmonization and coverage 17of existing analytical methods, the lack of automation of spectral data processing, and the data 18 interpretation [3]. These limitations are the major driving force providing impetus for the 19 development of a huge plethora of metabolomics tools, software, programs, and databases. 20Although excellent compilations are available for M...

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

Cited by 43 publications

References 63 publications

FlavonoidSearch: A system for comprehensive flavonoid annotation by mass spectrometry

FlavonoidSearch: A system for comprehensive flavonoid annotation by mass spectrometry

Characterization of unique metabolites in γ‐aminobutyric acid‐rich cheese by metabolome analysis using liquid chromatography‐mass spectrometry

Updates in metabolomics tools and resources: 2014–2015

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