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SHIFTX2: significantly improved protein chemical shift prediction

Overview of attention for article published in Journal of Biomolecular NMR, March 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#4 of 283)
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

blogs
1 blog
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
291 Dimensions

Readers on

mendeley
237 Mendeley
citeulike
4 CiteULike
Title
SHIFTX2: significantly improved protein chemical shift prediction
Published in
Journal of Biomolecular NMR, March 2011
DOI 10.1007/s10858-011-9478-4
Pubmed ID
Authors

Beomsoo Han, Yifeng Liu, Simon W. Ginzinger, David S. Wishart, Han B, Liu Y, Ginzinger SW, Wishart DS

Abstract

A new computer program, called SHIFTX2, is described which is capable of rapidly and accurately calculating diamagnetic (1)H, (13)C and (15)N chemical shifts from protein coordinate data. Compared to its predecessor (SHIFTX) and to other existing protein chemical shift prediction programs, SHIFTX2 is substantially more accurate (up to 26% better by correlation coefficient with an RMS error that is up to 3.3× smaller) than the next best performing program. It also provides significantly more coverage (up to 10% more), is significantly faster (up to 8.5×) and capable of calculating a wider variety of backbone and side chain chemical shifts (up to 6×) than many other shift predictors. In particular, SHIFTX2 is able to attain correlation coefficients between experimentally observed and predicted backbone chemical shifts of 0.9800 ((15)N), 0.9959 ((13)Cα), 0.9992 ((13)Cβ), 0.9676 ((13)C'), 0.9714 ((1)HN), 0.9744 ((1)Hα) and RMS errors of 1.1169, 0.4412, 0.5163, 0.5330, 0.1711, and 0.1231 ppm, respectively. The correlation between SHIFTX2's predicted and observed side chain chemical shifts is 0.9787 ((13)C) and 0.9482 ((1)H) with RMS errors of 0.9754 and 0.1723 ppm, respectively. SHIFTX2 is able to achieve such a high level of accuracy by using a large, high quality database of training proteins (>190), by utilizing advanced machine learning techniques, by incorporating many more features (χ(2) and χ(3) angles, solvent accessibility, H-bond geometry, pH, temperature), and by combining sequence-based with structure-based chemical shift prediction techniques. With this substantial improvement in accuracy we believe that SHIFTX2 will open the door to many long-anticipated applications of chemical shift prediction to protein structure determination, refinement and validation. SHIFTX2 is available both as a standalone program and as a web server ( http://www.shiftx2.ca ).

Mendeley readers

The data shown below were compiled from readership statistics for 237 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 4%
Germany 2 <1%
United Kingdom 2 <1%
France 2 <1%
Canada 1 <1%
Ireland 1 <1%
Brazil 1 <1%
Taiwan 1 <1%
Spain 1 <1%
Other 4 2%
Unknown 212 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 66 28%
Student > Ph. D. Student 64 27%
Student > Bachelor 38 16%
Professor > Associate Professor 13 5%
Unspecified 12 5%
Other 44 19%
Readers by discipline Count As %
Chemistry 81 34%
Agricultural and Biological Sciences 60 25%
Biochemistry, Genetics and Molecular Biology 42 18%
Unspecified 20 8%
Computer Science 13 5%
Other 21 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 29 August 2015.
All research outputs
#612,274
of 5,577,258 outputs
Outputs from Journal of Biomolecular NMR
#4
of 283 outputs
Outputs of similar age
#27,874
of 171,331 outputs
Outputs of similar age from Journal of Biomolecular NMR
#1
of 15 outputs
Altmetric has tracked 5,577,258 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 283 research outputs from this source. They receive a mean Attention Score of 1.9. This one has done particularly well, scoring higher than 98% 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 171,331 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 83% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.