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Chemical Basis of Metabolic Network Organization

Overview of attention for article published in PLoS Computational Biology, October 2011
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Title
Chemical Basis of Metabolic Network Organization
Published in
PLoS Computational Biology, October 2011
DOI 10.1371/journal.pcbi.1002214
Pubmed ID
Authors

Qiang Zhu, Tao Qin, Ying-Ying Jiang, Cong Ji, De-Xin Kong, Bin-Guang Ma, Hong-Yu Zhang

Abstract

Although the metabolic networks of the three domains of life consist of different constituents and metabolic pathways, they exhibit the same scale-free organization. This phenomenon has been hypothetically explained by preferential attachment principle that the new-recruited metabolites attach preferentially to those that are already well connected. However, since metabolites are usually small molecules and metabolic processes are basically chemical reactions, we speculate that the metabolic network organization may have a chemical basis. In this paper, chemoinformatic analyses on metabolic networks of Kyoto Encyclopedia of Genes and Genomes (KEGG), Escherichia coli and Saccharomyces cerevisiae were performed. It was found that there exist qualitative and quantitative correlations between network topology and chemical properties of metabolites. The metabolites with larger degrees of connectivity (hubs) are of relatively stronger polarity. This suggests that metabolic networks are chemically organized to a certain extent, which was further elucidated in terms of high concentrations required by metabolic hubs to drive a variety of reactions. This finding not only provides a chemical explanation to the preferential attachment principle for metabolic network expansion, but also has important implications for metabolic network design and metabolite concentration prediction.

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X Demographics

The data shown below were collected from the profiles of 2 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 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 9%
Portugal 1 1%
Singapore 1 1%
Brazil 1 1%
Japan 1 1%
Spain 1 1%
Unknown 64 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 37%
Student > Ph. D. Student 19 25%
Student > Master 6 8%
Professor 5 7%
Professor > Associate Professor 4 5%
Other 9 12%
Unknown 5 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 49%
Biochemistry, Genetics and Molecular Biology 10 13%
Computer Science 7 9%
Engineering 4 5%
Mathematics 3 4%
Other 6 8%
Unknown 9 12%
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 14 November 2011.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from PLoS Computational Biology
#7,480
of 8,960 outputs
Outputs of similar age
#104,173
of 148,228 outputs
Outputs of similar age from PLoS Computational Biology
#78
of 120 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 11th percentile – i.e., 11% 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 148,228 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.