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Toward better annotation in plant metabolomics: isolation and structure elucidation of 36 specialized metabolites from Oryza sativa (rice) by using MS/MS and NMR analyses

Overview of attention for article published in Metabolomics, December 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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9 X users
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1 Facebook page

Citations

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71 Dimensions

Readers on

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135 Mendeley
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1 CiteULike
Title
Toward better annotation in plant metabolomics: isolation and structure elucidation of 36 specialized metabolites from Oryza sativa (rice) by using MS/MS and NMR analyses
Published in
Metabolomics, December 2013
DOI 10.1007/s11306-013-0619-5
Pubmed ID
Authors

Zhigang Yang, Ryo Nakabayashi, Yozo Okazaki, Tetsuya Mori, Satoshi Takamatsu, Susumu Kitanaka, Jun Kikuchi, Kazuki Saito

Abstract

Metabolomics plays an important role in phytochemical genomics and crop breeding; however, metabolite annotation is a significant bottleneck in metabolomic studies. In particular, in liquid chromatography-mass spectrometry (MS)-based metabolomics, which has become a routine technology for the profiling of plant-specialized metabolites, a substantial number of metabolites detected as MS peaks are still not assigned properly to a single metabolite. Oryza sativa (rice) is one of the most important staple crops in the world. In the present study, we isolated and elucidated the structures of specialized metabolites from rice by using MS/MS and NMR. Thirty-six compounds, including five new flavonoids and eight rare flavonolignan isomers, were isolated from the rice leaves. The MS/MS spectral data of the isolated compounds, with a detailed interpretation of MS fragmentation data, will facilitate metabolite annotation of the related phytochemicals by enriching the public mass spectral data depositories, including the plant-specific MS/MS-based database, ReSpect.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
Italy 1 <1%
Belgium 1 <1%
Brazil 1 <1%
Unknown 131 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 23%
Researcher 22 16%
Student > Bachelor 15 11%
Student > Master 15 11%
Lecturer 7 5%
Other 23 17%
Unknown 22 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 30%
Chemistry 23 17%
Biochemistry, Genetics and Molecular Biology 21 16%
Engineering 4 3%
Pharmacology, Toxicology and Pharmaceutical Science 3 2%
Other 13 10%
Unknown 30 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 September 2021.
All research outputs
#5,569,163
of 22,758,963 outputs
Outputs from Metabolomics
#290
of 1,292 outputs
Outputs of similar age
#64,480
of 305,815 outputs
Outputs of similar age from Metabolomics
#3
of 18 outputs
Altmetric has tracked 22,758,963 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,292 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 305,815 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.