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The B6 database: a tool for the description and classification of vitamin B6-dependent enzymatic activities and of the corresponding protein families

Overview of attention for article published in BMC Bioinformatics, September 2009
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)

Mentioned by

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1 tweeter

Citations

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187 Dimensions

Readers on

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182 Mendeley

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Title
The B6 database: a tool for the description and classification of vitamin B6-dependent enzymatic activities and of the corresponding protein families
Published in
BMC Bioinformatics, September 2009
DOI 10.1186/1471-2105-10-273
Pubmed ID
19723314
Authors

Riccardo Percudani, Alessio Peracchi

Abstract

Enzymes that depend on vitamin B6 (and in particular on its metabolically active form, pyridoxal 5'-phosphate, PLP) are of great relevance to biology and medicine, as they catalyze a wide variety of biochemical reactions mainly involving amino acid substrates. Although PLP-dependent enzymes belong to a small number of independent evolutionary lineages, they encompass more than 160 distinct catalytic functions, thus representing a striking example of divergent evolution. The importance and remarkable versatility of these enzymes, as well as the difficulties in their functional classification, create a need for an integrated source of information about them.

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

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Japan 1 <1%
Netherlands 1 <1%
Germany 1 <1%
Unknown 177 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 28%
Student > Bachelor 25 14%
Researcher 23 13%
Student > Master 21 12%
Student > Doctoral Student 13 7%
Other 22 12%
Unknown 27 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 50 27%
Agricultural and Biological Sciences 42 23%
Chemistry 32 18%
Medicine and Dentistry 10 5%
Immunology and Microbiology 4 2%
Other 12 7%
Unknown 32 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 31 July 2014.
All research outputs
#1,994,511
of 4,506,051 outputs
Outputs from BMC Bioinformatics
#1,491
of 2,646 outputs
Outputs of similar age
#43,899
of 109,724 outputs
Outputs of similar age from BMC Bioinformatics
#85
of 123 outputs
Altmetric has tracked 4,506,051 research outputs across all sources so far. This one has received more attention than most of these and is in the 53rd percentile.
So far Altmetric has tracked 2,646 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 39th percentile – i.e., 39% 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 109,724 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.
We're also able to compare this research output to 123 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.

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