An approach to peak detection in GC-MS chromatograms and application of KNApSAcK database in prediction of candidate metabolites

Takashi Oishi; Ken Ichi Tanaka; Takuya Hashimoto; Yoko Shinbo; Kanokwan Jumtee; Takeshi Bamba; Eiichiro Fukusaki; Hideyuki Suzuki; Daisuke Shibata; Hiroki Takahashi; Hiroko Asahi; Ken Kurokawa; Yukiko Nakamura; Aki Hirai; Kensuke Nakamura; Md Altaf-Ul-Amin; Shigehiko Kanaya

doi:10.5511/plantbiotechnology.26.167

An approach to peak detection in GC-MS chromatograms and application of KNApSAcK database in prediction of candidate metabolites

Takashi Oishi, Ken Ichi Tanaka, Takuya Hashimoto, Yoko Shinbo, Kanokwan Jumtee, Takeshi Bamba, Eiichiro Fukusaki, Hideyuki Suzuki, Daisuke Shibata, Hiroki Takahashi, Hiroko Asahi, Ken Kurokawa, Yukiko Nakamura, Aki Hirai, Kensuke Nakamura, Md Altaf-Ul-Amin, Shigehiko Kanaya

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

Since 2004, we have been developing a metabolite database concerning species-metabolite relations called KNApSAcK, which currently contains 49,165 species-metabolite relations incorporating 24,847 metabolites. In the present study, we report current status of KNApSAcK database and it's application to metabolomics fields and propose a new algorithm for detecting fragmentation patterns in a complicated mixture such as a plant tissue and a new scheme for analyzing spectral information leading to peak annotation of GC-MS spectra. When considering samples corresponding to a variety of species in addition to model species, KNApSAcK DB has strong potential for contribution to metabolomics research by way of applying it not only to simple metabolite search but also to further metabolomics analysis.

Original language	English
Pages (from-to)	167-174
Number of pages	8
Journal	Plant Biotechnology
Volume	26
Issue number	1
DOIs	https://doi.org/10.5511/plantbiotechnology.26.167
Publication status	Published - 2009
Externally published	Yes

All Science Journal Classification (ASJC) codes

Biotechnology
Agronomy and Crop Science
Plant Science

Access to Document

10.5511/plantbiotechnology.26.167

Cite this

Oishi, T., Tanaka, K. I., Hashimoto, T., Shinbo, Y., Jumtee, K., Bamba, T., Fukusaki, E., Suzuki, H., Shibata, D., Takahashi, H., Asahi, H., Kurokawa, K., Nakamura, Y., Hirai, A., Nakamura, K., Altaf-Ul-Amin, M., & Kanaya, S. (2009). An approach to peak detection in GC-MS chromatograms and application of KNApSAcK database in prediction of candidate metabolites. Plant Biotechnology, 26(1), 167-174. https://doi.org/10.5511/plantbiotechnology.26.167

Oishi, T, Tanaka, KI, Hashimoto, T, Shinbo, Y, Jumtee, K, Bamba, T, Fukusaki, E, Suzuki, H, Shibata, D, Takahashi, H, Asahi, H, Kurokawa, K, Nakamura, Y, Hirai, A, Nakamura, K, Altaf-Ul-Amin, M & Kanaya, S 2009, 'An approach to peak detection in GC-MS chromatograms and application of KNApSAcK database in prediction of candidate metabolites', Plant Biotechnology, vol. 26, no. 1, pp. 167-174. https://doi.org/10.5511/plantbiotechnology.26.167

@article{342b61e559874885a294028138cdbc0d,

title = "An approach to peak detection in GC-MS chromatograms and application of KNApSAcK database in prediction of candidate metabolites",

abstract = "Since 2004, we have been developing a metabolite database concerning species-metabolite relations called KNApSAcK, which currently contains 49,165 species-metabolite relations incorporating 24,847 metabolites. In the present study, we report current status of KNApSAcK database and it's application to metabolomics fields and propose a new algorithm for detecting fragmentation patterns in a complicated mixture such as a plant tissue and a new scheme for analyzing spectral information leading to peak annotation of GC-MS spectra. When considering samples corresponding to a variety of species in addition to model species, KNApSAcK DB has strong potential for contribution to metabolomics research by way of applying it not only to simple metabolite search but also to further metabolomics analysis.",

author = "Takashi Oishi and Tanaka, {Ken Ichi} and Takuya Hashimoto and Yoko Shinbo and Kanokwan Jumtee and Takeshi Bamba and Eiichiro Fukusaki and Hideyuki Suzuki and Daisuke Shibata and Hiroki Takahashi and Hiroko Asahi and Ken Kurokawa and Yukiko Nakamura and Aki Hirai and Kensuke Nakamura and Md Altaf-Ul-Amin and Shigehiko Kanaya",

year = "2009",

doi = "10.5511/plantbiotechnology.26.167",

language = "English",

volume = "26",

pages = "167--174",

journal = "Plant Biotechnology",

issn = "1342-4580",

publisher = "Japanese Society for Plant Cell and Molecular Biology",

number = "1",

}

TY - JOUR

T1 - An approach to peak detection in GC-MS chromatograms and application of KNApSAcK database in prediction of candidate metabolites

AU - Oishi, Takashi

AU - Tanaka, Ken Ichi

AU - Hashimoto, Takuya

AU - Shinbo, Yoko

AU - Jumtee, Kanokwan

AU - Bamba, Takeshi

AU - Fukusaki, Eiichiro

AU - Suzuki, Hideyuki

AU - Shibata, Daisuke

AU - Takahashi, Hiroki

AU - Asahi, Hiroko

AU - Kurokawa, Ken

AU - Nakamura, Yukiko

AU - Hirai, Aki

AU - Nakamura, Kensuke

AU - Altaf-Ul-Amin, Md

AU - Kanaya, Shigehiko

PY - 2009

Y1 - 2009

N2 - Since 2004, we have been developing a metabolite database concerning species-metabolite relations called KNApSAcK, which currently contains 49,165 species-metabolite relations incorporating 24,847 metabolites. In the present study, we report current status of KNApSAcK database and it's application to metabolomics fields and propose a new algorithm for detecting fragmentation patterns in a complicated mixture such as a plant tissue and a new scheme for analyzing spectral information leading to peak annotation of GC-MS spectra. When considering samples corresponding to a variety of species in addition to model species, KNApSAcK DB has strong potential for contribution to metabolomics research by way of applying it not only to simple metabolite search but also to further metabolomics analysis.

AB - Since 2004, we have been developing a metabolite database concerning species-metabolite relations called KNApSAcK, which currently contains 49,165 species-metabolite relations incorporating 24,847 metabolites. In the present study, we report current status of KNApSAcK database and it's application to metabolomics fields and propose a new algorithm for detecting fragmentation patterns in a complicated mixture such as a plant tissue and a new scheme for analyzing spectral information leading to peak annotation of GC-MS spectra. When considering samples corresponding to a variety of species in addition to model species, KNApSAcK DB has strong potential for contribution to metabolomics research by way of applying it not only to simple metabolite search but also to further metabolomics analysis.

UR - http://www.scopus.com/inward/record.url?scp=66649110571&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=66649110571&partnerID=8YFLogxK

U2 - 10.5511/plantbiotechnology.26.167

DO - 10.5511/plantbiotechnology.26.167

M3 - Article

AN - SCOPUS:66649110571

SN - 1342-4580

VL - 26

SP - 167

EP - 174

JO - Plant Biotechnology

JF - Plant Biotechnology

IS - 1

ER -

An approach to peak detection in GC-MS chromatograms and application of KNApSAcK database in prediction of candidate metabolites

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this