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The SDR (short-chain dehydrogenase/reductase and related enzymes) nomenclature initiative

Overview of attention for article published in Chemico-Biological Interactions, November 2008
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

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2 patents
wikipedia
52 Wikipedia pages

Citations

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335 Dimensions

Readers on

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248 Mendeley
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1 CiteULike
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Title
The SDR (short-chain dehydrogenase/reductase and related enzymes) nomenclature initiative
Published in
Chemico-Biological Interactions, November 2008
DOI 10.1016/j.cbi.2008.10.040
Pubmed ID
Authors

Bengt Persson, Yvonne Kallberg, James E. Bray, Elspeth Bruford, Stephen L. Dellaporta, Angelo D. Favia, Roser Gonzalez Duarte, Hans Jörnvall, Kathryn L. Kavanagh, Natalia Kedishvili, Michael Kisiela, Edmund Maser, Rebekka Mindnich, Sandra Orchard, Trevor M. Penning, Janet M. Thornton, Jerzy Adamski, Udo Oppermann

Abstract

Short-chain dehydrogenases/reductases (SDR) constitute one of the largest enzyme superfamilies with presently over 46,000 members. In phylogenetic comparisons, members of this superfamily show early divergence where the majority have only low pairwise sequence identity, although sharing common structural properties. The SDR enzymes are present in virtually all genomes investigated, and in humans over 70 SDR genes have been identified. In humans, these enzymes are involved in the metabolism of a large variety of compounds, including steroid hormones, prostaglandins, retinoids, lipids and xenobiotics. It is now clear that SDRs represent one of the oldest protein families and contribute to essential functions and interactions of all forms of life. As this field continues to grow rapidly, a systematic nomenclature is essential for future annotation and reference purposes. A functional subdivision of the SDR superfamily into at least 200 SDR families based upon hidden Markov models forms a suitable foundation for such a nomenclature system, which we present in this paper using human SDRs as examples.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 248 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 1%
United Kingdom 2 <1%
Pakistan 1 <1%
Ireland 1 <1%
Austria 1 <1%
Malaysia 1 <1%
Canada 1 <1%
Romania 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 235 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 60 24%
Researcher 46 19%
Student > Master 39 16%
Other 13 5%
Student > Doctoral Student 13 5%
Other 38 15%
Unknown 39 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 100 40%
Biochemistry, Genetics and Molecular Biology 59 24%
Chemistry 8 3%
Medicine and Dentistry 7 3%
Pharmacology, Toxicology and Pharmaceutical Science 6 2%
Other 22 9%
Unknown 46 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 21 August 2023.
All research outputs
#3,798,611
of 25,374,647 outputs
Outputs from Chemico-Biological Interactions
#179
of 2,726 outputs
Outputs of similar age
#12,506
of 105,310 outputs
Outputs of similar age from Chemico-Biological Interactions
#2
of 26 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,726 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 91% 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 105,310 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 84% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.