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A curated C. difficile strain 630 metabolic network: prediction of essential targets and inhibitors

Overview of attention for article published in BMC Systems Biology, October 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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1 blog
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6 X users

Citations

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40 Dimensions

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73 Mendeley
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2 CiteULike
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Title
A curated C. difficile strain 630 metabolic network: prediction of essential targets and inhibitors
Published in
BMC Systems Biology, October 2014
DOI 10.1186/s12918-014-0117-z
Pubmed ID
Authors

Mathieu Larocque, Thierry Chénard, Rafael Najmanovich

Abstract

Background Clostridium difficile is the leading cause of hospital-borne infections occurring when the natural intestinal flora is depleted following antibiotic treatment. Current treatments for Clostridium difficile infections present high relapse rates and new hyper-virulent and multi-resistant strains are emerging, making the study of this nosocomial pathogen necessary to find novel therapeutic targets.ResultsWe present iMLTC806cdf, an extensively curated reconstructed metabolic network for the C. difficile pathogenic strain 630. iMLTC806cdf contains 806 genes, 703 metabolites and 769 metabolic, 117 exchange and 145 transport reactions. iMLTC806cdf is the most complete and accurate metabolic reconstruction of a gram-positive anaerobic bacteria to date. We validate the model with simulated growth assays in different media and carbon sources and use it to predict essential genes. We obtain 89.2% accuracy in the prediction of gene essentiality when compared to experimental data for B. subtilis homologs (the closest organism for which such data exists). We predict the existence of 76 essential genes and 39 essential gene pairs, a number of which are unique to C. difficile and have non-existing or predicted non-essential human homologs. For 29 of these potential therapeutic targets, we find 125 inhibitors of homologous proteins including approved drugs with the potential for drug repositioning, that when validated experimentally could serve as starting points in the development of new antibiotics.ConclusionsWe created a highly curated metabolic network model of C. difficile strain 630 and used it to predict essential genes as potential new therapeutic targets in the fight against Clostridium difficile infections.

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X Demographics

The data shown below were collected from the profiles of 6 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 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Colombia 1 1%
Unknown 71 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 25%
Researcher 17 23%
Student > Master 10 14%
Student > Bachelor 7 10%
Professor > Associate Professor 4 5%
Other 7 10%
Unknown 10 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 30%
Biochemistry, Genetics and Molecular Biology 10 14%
Computer Science 5 7%
Immunology and Microbiology 5 7%
Engineering 4 5%
Other 12 16%
Unknown 15 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 16 January 2015.
All research outputs
#3,090,385
of 23,881,329 outputs
Outputs from BMC Systems Biology
#84
of 1,126 outputs
Outputs of similar age
#35,441
of 258,256 outputs
Outputs of similar age from BMC Systems Biology
#3
of 29 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,126 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 92% 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 258,256 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 86% of its contemporaries.
We're also able to compare this research output to 29 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 93% of its contemporaries.