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Genome-scale metabolic reconstructions of Bifidobacterium adolescentis L2-32 and Faecalibacterium prausnitzii A2-165 and their interaction

Overview of attention for article published in BMC Systems Biology, April 2014
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Mentioned by

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1 tweeter

Citations

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73 Dimensions

Readers on

mendeley
243 Mendeley
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1 CiteULike
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Title
Genome-scale metabolic reconstructions of Bifidobacterium adolescentis L2-32 and Faecalibacterium prausnitzii A2-165 and their interaction
Published in
BMC Systems Biology, April 2014
DOI 10.1186/1752-0509-8-41
Pubmed ID
Authors

Ibrahim E El-Semman, Fredrik H Karlsson, Saeed Shoaie, Intawat Nookaew, Taysir H Soliman, Jens Nielsen

Abstract

The gut microbiota plays an important role in human health and disease by acting as a metabolic organ. Metagenomic sequencing has shown how dysbiosis in the gut microbiota is associated with human metabolic diseases such as obesity and diabetes. Modeling may assist to gain insight into the metabolic implication of an altered microbiota. Fast and accurate reconstruction of metabolic models for members of the gut microbiota, as well as methods to simulate a community of microorganisms, are therefore needed. The Integrated Microbial Genomes (IMG) database contains functional annotation for nearly 4,650 bacterial genomes. This tremendous new genomic information adds new opportunities for systems biology to reconstruct accurate genome scale metabolic models (GEMs).

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 243 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
Italy 1 <1%
Latvia 1 <1%
United Kingdom 1 <1%
Switzerland 1 <1%
Iran, Islamic Republic of 1 <1%
Singapore 1 <1%
Spain 1 <1%
Denmark 1 <1%
Other 0 0%
Unknown 231 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 60 25%
Student > Ph. D. Student 46 19%
Student > Master 36 15%
Student > Bachelor 13 5%
Student > Doctoral Student 12 5%
Other 35 14%
Unknown 41 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 76 31%
Biochemistry, Genetics and Molecular Biology 32 13%
Immunology and Microbiology 19 8%
Medicine and Dentistry 15 6%
Engineering 14 6%
Other 33 14%
Unknown 54 22%

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 28 August 2014.
All research outputs
#12,357,523
of 18,796,975 outputs
Outputs from BMC Systems Biology
#637
of 1,127 outputs
Outputs of similar age
#115,846
of 210,202 outputs
Outputs of similar age from BMC Systems Biology
#1
of 3 outputs
Altmetric has tracked 18,796,975 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,127 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 33rd percentile – i.e., 33% 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 210,202 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
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. This one has scored higher than all of them