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Use of the University of Minnesota Biocatalysis/Biodegradation Database for study of microbial degradation

Overview of attention for article published in Microbial Informatics and Experimentation, January 2012
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1 tweeter

Citations

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40 Dimensions

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80 Mendeley
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Title
Use of the University of Minnesota Biocatalysis/Biodegradation Database for study of microbial degradation
Published in
Microbial Informatics and Experimentation, January 2012
DOI 10.1186/2042-5783-2-1
Pubmed ID
Authors

Lynda BM Ellis, Lawrence P Wackett

Abstract

Microorganisms are ubiquitous on earth and have diverse metabolic transformative capabilities important for environmental biodegradation of chemicals that helps maintain ecosystem and human health. Microbial biodegradative metabolism is the main focus of the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD). UM-BBD data has also been used to develop a computational metabolic pathway prediction system that can be applied to chemicals for which biodegradation data is currently lacking. The UM-Pathway Prediction System (UM-PPS) relies on metabolic rules that are based on organic functional groups and predicts plausible biodegradative metabolism. The predictions are useful to environmental chemists that look for metabolic intermediates, for regulators looking for potential toxic products, for microbiologists seeking to understand microbial biodegradation, and others with a wide-range of interests.

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 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
Poland 1 1%
Brazil 1 1%
Unknown 76 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 26%
Student > Master 11 14%
Researcher 10 13%
Professor 7 9%
Student > Bachelor 6 8%
Other 14 18%
Unknown 11 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 24%
Environmental Science 13 16%
Biochemistry, Genetics and Molecular Biology 9 11%
Chemistry 7 9%
Engineering 7 9%
Other 7 9%
Unknown 18 23%

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 09 October 2012.
All research outputs
#11,053,306
of 12,434,464 outputs
Outputs from Microbial Informatics and Experimentation
#15
of 15 outputs
Outputs of similar age
#109,318
of 128,800 outputs
Outputs of similar age from Microbial Informatics and Experimentation
#1
of 1 outputs
Altmetric has tracked 12,434,464 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.7. This one scored the same or higher as 0 of them.
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 128,800 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 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