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NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation

Overview of attention for article published in BMC Bioinformatics, May 2015
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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 (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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Citations

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83 Dimensions

Readers on

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194 Mendeley
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2 CiteULike
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Title
NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation
Published in
BMC Bioinformatics, May 2015
DOI 10.1186/s12859-015-0588-y
Pubmed ID
Authors

Roie Levy, Rogan Carr, Anat Kreimer, Shiri Freilich, Elhanan Borenstein

Abstract

Host-microbe and microbe-microbe interactions are often governed by the complex exchange of metabolites. Such interactions play a key role in determining the way pathogenic and commensal species impact their host and in the assembly of complex microbial communities. Recently, several studies have demonstrated how such interactions are reflected in the organization of the metabolic networks of the interacting species, and introduced various graph theory-based methods to predict host-microbe and microbe-microbe interactions directly from network topology. Using these methods, such studies have revealed evolutionary and ecological processes that shape species interactions and community assembly, highlighting the potential of this reverse-ecology research paradigm. NetCooperate is a web-based tool and a software package for determining host-microbe and microbe-microbe cooperative potential. It specifically calculates two previously developed and validated metrics for species interaction: the Biosynthetic Support Score which quantifies the ability of a host species to supply the nutritional requirements of a parasitic or a commensal species, and the Metabolic Complementarity Index which quantifies the complementarity of a pair of microbial organisms' niches. NetCooperate takes as input a pair of metabolic networks, and returns the pairwise metrics as well as a list of potential syntrophic metabolic compounds. The Biosynthetic Support Score and Metabolic Complementarity Index provide insight into host-microbe and microbe-microbe metabolic interactions. NetCooperate determines these interaction indices from metabolic network topology, and can be used for small- or large-scale analyses. NetCooperate is provided as both a web-based tool and an open-source Python module; both are freely available online at http://elbo.gs.washington.edu/software_netcooperate.html.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 194 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 1%
United States 2 1%
Canada 1 <1%
India 1 <1%
Japan 1 <1%
Singapore 1 <1%
Unknown 186 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 47 24%
Researcher 43 22%
Student > Bachelor 26 13%
Student > Master 24 12%
Student > Doctoral Student 11 6%
Other 23 12%
Unknown 20 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 73 38%
Biochemistry, Genetics and Molecular Biology 36 19%
Computer Science 19 10%
Environmental Science 10 5%
Immunology and Microbiology 6 3%
Other 25 13%
Unknown 25 13%
Attention Score in Context

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 25 May 2015.
All research outputs
#5,254,863
of 24,885,505 outputs
Outputs from BMC Bioinformatics
#1,902
of 7,601 outputs
Outputs of similar age
#61,812
of 270,925 outputs
Outputs of similar age from BMC Bioinformatics
#35
of 119 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,601 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 74% 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 270,925 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 77% of its contemporaries.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.