Report for: The evolution of metabolic networks of E. coli

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Title	The evolution of metabolic networks of E. coli
Published in	BMC Systems Biology, January 2011
DOI	10.1186/1752-0509-5-182
Pubmed ID	22044664
Authors	David J Baumler, Roman G Peplinski, Jennifer L Reed, Jeremy D Glasner, Nicole T Perna
Abstract	Despite the availability of numerous complete genome sequences from E. coli strains, published genome-scale metabolic models exist only for two commensal E. coli strains. These models have proven useful for many applications, such as engineering strains for desired product formation, and we sought to explore how constructing and evaluating additional metabolic models for E. coli strains could enhance these efforts.

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Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Geographical breakdown

Country	Count	As %
Unknown	5	100%

Demographic breakdown

Type	Count	As %
Members of the public	4	80%
Scientists	1	20%

Mendeley readers

The data shown below were compiled from readership statistics for 245 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country	Count	As %
United States	11	4%
United Kingdom	2	<1%
Denmark	2	<1%
Indonesia	1	<1%
Sweden	1	<1%
Chile	1	<1%
Switzerland	1	<1%
Germany	1	<1%
Mexico	1	<1%
Other	6	2%
Unknown	218	89%

Demographic breakdown

Readers by professional status	Count	As %
Student > Ph. D. Student	74	30%
Researcher	48	20%
Student > Master	26	11%
Student > Bachelor	26	11%
Student > Doctoral Student	13	5%
Other	40	16%
Unknown	18	7%

Readers by discipline	Count	As %
Agricultural and Biological Sciences	116	47%
Biochemistry, Genetics and Molecular Biology	34	14%
Engineering	18	7%
Computer Science	15	6%
Medicine and Dentistry	8	3%
Other	29	12%
Unknown	25	10%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 September 2014.

All research outputs

#5,502,067

of 22,655,397 outputs

Outputs from BMC Systems Biology

#173

of 1,142 outputs

Outputs of similar age

#40,281

of 180,260 outputs

Outputs of similar age from BMC Systems Biology

of 40 outputs

Altmetric has tracked 22,655,397 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.

So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done well, scoring higher than 84% 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 180,260 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 40 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.

The evolution of metabolic networks of E. coli

About this Attention Score

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Geographical breakdown

Demographic breakdown

Mendeley readers

Geographical breakdown

Demographic breakdown

Attention Score in Context