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Experimental design and reporting standards for metabolomics studies of mammalian cell lines

Overview of attention for article published in Cellular & Molecular Life Sciences, July 2017
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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 (75th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

twitter
10 tweeters

Citations

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12 Dimensions

Readers on

mendeley
44 Mendeley
Title
Experimental design and reporting standards for metabolomics studies of mammalian cell lines
Published in
Cellular & Molecular Life Sciences, July 2017
DOI 10.1007/s00018-017-2582-1
Pubmed ID
Authors

Sarah Hayton, Garth L. Maker, Ian Mullaney, Robert D. Trengove

Abstract

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 32%
Researcher 8 18%
Unspecified 7 16%
Student > Master 5 11%
Student > Postgraduate 2 5%
Other 8 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 32%
Pharmacology, Toxicology and Pharmaceutical Science 7 16%
Unspecified 7 16%
Agricultural and Biological Sciences 5 11%
Chemistry 5 11%
Other 6 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 05 July 2017.
All research outputs
#1,863,359
of 11,430,110 outputs
Outputs from Cellular & Molecular Life Sciences
#299
of 2,420 outputs
Outputs of similar age
#63,109
of 260,293 outputs
Outputs of similar age from Cellular & Molecular Life Sciences
#5
of 59 outputs
Altmetric has tracked 11,430,110 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,420 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 87% 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 260,293 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 75% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.