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Between Metabolite Relationships: an essential aspect of metabolic change

Overview of attention for article published in Metabolomics, May 2011
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Title
Between Metabolite Relationships: an essential aspect of metabolic change
Published in
Metabolomics, May 2011
DOI 10.1007/s11306-011-0316-1
Pubmed ID
Authors

Jeroen J. Jansen, Ewa Szymańska, Huub C. J. Hoefsloot, Doris M. Jacobs, Katrin Strassburg, Age K. Smilde

Abstract

Not only the levels of individual metabolites, but also the relations between the levels of different metabolites may indicate (experimentally induced) changes in a biological system. Component analysis methods in current 'standard' use for metabolomics, such as Principal Component Analysis (PCA), do not focus on changes in these relations. We therefore propose the concept of 'Between Metabolite Relationships' (BMRs): common changes in the covariance (or correlation) between all metabolites in an organism. Such structural changes may indicate metabolic change brought about by experimental manipulation but which are lost with standard data analysis methods. These BMRs can be analysed by the INdividual Differences SCALing (INDSCAL) method. First the BMR quantification is described and subsequently the INDSCAL method. Finally, two studies illustrate the power and the applicability of BMRs in metabolomics. The first study is about the induced plant response of cabbage to herbivory, of which BMRs are a considerable part. In the second study-a human nutritional intervention study of green tea extract-standard data analysis tools did not reveal any metabolic change, although the BMRs were considerably affected. The presented results show that BMRs can be easily implemented in a wide variety of metabolomic studies. They provide a new source of information to describe biological systems in a way that fits flawlessly into the next generation of systems biology questions, dealing with personalized responses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0316-1) contains supplementary material, which is available to authorized users.

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Mendeley readers

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Geographical breakdown

Country Count As %
Germany 3 3%
Portugal 1 1%
Switzerland 1 1%
Netherlands 1 1%
France 1 1%
Brazil 1 1%
South Africa 1 1%
Finland 1 1%
Canada 1 1%
Other 2 2%
Unknown 86 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 30%
Researcher 24 24%
Student > Postgraduate 6 6%
Student > Master 6 6%
Student > Doctoral Student 6 6%
Other 21 21%
Unknown 6 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 39%
Chemistry 13 13%
Biochemistry, Genetics and Molecular Biology 11 11%
Computer Science 7 7%
Medicine and Dentistry 4 4%
Other 19 19%
Unknown 6 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 31 May 2012.
All research outputs
#18,308,895
of 22,668,244 outputs
Outputs from Metabolomics
#1,070
of 1,288 outputs
Outputs of similar age
#95,734
of 111,888 outputs
Outputs of similar age from Metabolomics
#5
of 12 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,288 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 4th percentile – i.e., 4% of its peers scored the same or lower than it.
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We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.