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Mass Spectrometry Based Molecular 3D-Cartography of Plant Metabolites

Overview of attention for article published in Frontiers in Plant Science, March 2017
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Title
Mass Spectrometry Based Molecular 3D-Cartography of Plant Metabolites
Published in
Frontiers in Plant Science, March 2017
DOI 10.3389/fpls.2017.00429
Pubmed ID
Authors

Dimitrios J. Floros, Daniel Petras, Clifford A. Kapono, Alexey V. Melnik, Tie-Jun Ling, Rob Knight, Pieter C. Dorrestein

Abstract

Plants play an essential part in global carbon fixing through photosynthesis and are the primary food and energy source for humans. Understanding them thoroughly is therefore of highest interest for humanity. Advances in DNA and RNA sequencing and in protein and metabolite analysis allow the systematic description of plant composition at the molecular level. With imaging mass spectrometry, we can now add a spatial level, typically in the micrometer-to-centimeter range, to their compositions, essential for a detailed molecular understanding. Here we present an LC-MS based approach for 3D plant imaging, which is scalable and allows the analysis of entire plants. We applied this approach in a case study to pepper and tomato plants. Together with MS/MS spectra library matching and spectral networking, this non-targeted workflow provides the highest sensitivity and selectivity for the molecular annotations and imaging of plants, laying the foundation for studies of plant metabolism and plant-environment interactions.

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The data shown below were collected from the profiles of 5 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 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 80 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 26%
Researcher 10 13%
Student > Master 10 13%
Student > Bachelor 8 10%
Other 5 6%
Other 13 16%
Unknown 13 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 33%
Chemistry 15 19%
Biochemistry, Genetics and Molecular Biology 6 8%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Engineering 3 4%
Other 9 11%
Unknown 17 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 14 April 2017.
All research outputs
#14,929,731
of 22,963,381 outputs
Outputs from Frontiers in Plant Science
#9,348
of 20,392 outputs
Outputs of similar age
#184,132
of 308,769 outputs
Outputs of similar age from Frontiers in Plant Science
#300
of 535 outputs
Altmetric has tracked 22,963,381 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,392 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
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 308,769 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 535 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.