In silico annotation of discriminative markers of three Zanthoxylum species using molecular network derived annotation propagation. (15th October 2019)
- Record Type:
- Journal Article
- Title:
- In silico annotation of discriminative markers of three Zanthoxylum species using molecular network derived annotation propagation. (15th October 2019)
- Main Title:
- In silico annotation of discriminative markers of three Zanthoxylum species using molecular network derived annotation propagation
- Authors:
- Lee, Jiho
da Silva, Ricardo R.
Jang, Hyeon Seok
Kim, Hyun Woo
Kwon, Yong Soo
Kim, Jung-Hwan
Yang, Heejung - Abstract:
- Highlights: The molecular networking and in silico annotation methods were applied for the variables annotation in Zanthoxlyum samples. Two in silico annotation tools, NAP and ClassyFire, helped the global classification of metabolites. Hesperidin and poncirin were tentatively annotated as the discriminant markers between Zanthoxlyum samples. Z. bungeanum and Z. piperitum were more closely related than Z. schinifolium . Abstract: In liquid chromatography-mass spectrometry (LC-MS) metabolomics, data matrices with up to thousands of variables for each ion peak are subjected to multivariate analysis (MVA) to assess the homogeneity between samples. The large dimensions of LC/MS datasets hinder the identification of the discriminant or the metabolic markers. In the present study, the molecular network (MN) approach and two in silico annotation tools, network annotation propagation (NAP) and the hierarchical chemical classification method, ClassyFire, were used to annotate the metabolites of three Zanthoxylum species, Z. bungeanum, Z. schinifolium and Z. piperitum . The in silico annotation results of the MN nodes and the MVA variables were combined and visualized in loading plots. This approach helped intuitive detection of the variables that greatly contributed to the separation of the samples in the score plot as discriminant or metabolic markers, thereby allowing rapid annotation of two flavanone derivatives.
- Is Part Of:
- Food chemistry. Volume 295(2019)
- Journal:
- Food chemistry
- Issue:
- Volume 295(2019)
- Issue Display:
- Volume 295, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 295
- Issue:
- 2019
- Issue Sort Value:
- 2019-0295-2019-0000
- Page Start:
- 368
- Page End:
- 376
- Publication Date:
- 2019-10-15
- Subjects:
- LC/MS -- Multivariate analysis -- Molecular network -- Zanthoxylum species
Food -- Analysis -- Periodicals
Food -- Composition -- Periodicals
664 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03088146 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.foodchem.2019.05.099 ↗
- Languages:
- English
- ISSNs:
- 0308-8146
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3977.284000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 10968.xml