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Computational modeling of sphingolipid metabolism

Overview of attention for article published in BMC Systems Biology, August 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)

Mentioned by

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4 tweeters
facebook
1 Facebook page

Citations

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12 Dimensions

Readers on

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47 Mendeley
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Title
Computational modeling of sphingolipid metabolism
Published in
BMC Systems Biology, August 2015
DOI 10.1186/s12918-015-0176-9
Pubmed ID
Authors

Weronika Wronowska, Agata Charzyńska, Karol Nienałtowski, Anna Gambin

Abstract

As suggested by the origin of the word, sphingolipids are mysterious molecules with various roles in antagonistic cellular processes such as autophagy, apoptosis, proliferation and differentiation. Moreover, sphingolipids have recently been recognized as important messengers in cellular signaling pathways. Notably, sphingolipid metabolism disorders have been observed in various pathological conditions such as cancer and neurodegeneration. The existing formal models of sphingolipid metabolism focus mainly on de novo ceramide synthesis or are limited to biochemical transformations of particular subspecies. Here, we propose the first comprehensive computational model of sphingolipid metabolism in human tissue. Contrary to the previous approaches, we use a model that reflects cell compartmentalization thereby highlighting the differences among individual organelles. The model that we present here was validated using recently proposed methods of model analysis, allowing to detect the most sensitive and experimentally non-identifiable parameters and determine the main sources of model variance. Moreover, we demonstrate the usefulness of our model in the study of molecular processes underlying Alzheimer's disease, which are associated with sphingolipid metabolism.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
United States 1 2%
Portugal 1 2%
Unknown 44 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 28%
Researcher 8 17%
Student > Ph. D. Student 7 15%
Student > Bachelor 4 9%
Lecturer 3 6%
Other 7 15%
Unknown 5 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 26%
Biochemistry, Genetics and Molecular Biology 10 21%
Chemistry 5 11%
Medicine and Dentistry 2 4%
Mathematics 2 4%
Other 10 21%
Unknown 6 13%

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 28 March 2016.
All research outputs
#9,436,596
of 16,400,568 outputs
Outputs from BMC Systems Biology
#464
of 1,106 outputs
Outputs of similar age
#106,380
of 237,713 outputs
Outputs of similar age from BMC Systems Biology
#2
of 3 outputs
Altmetric has tracked 16,400,568 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,106 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 55% 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 237,713 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.