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FragIt: A Tool to Prepare Input Files for Fragment Based Quantum Chemical Calculations

Overview of attention for article published in PLOS ONE, September 2012
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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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

blogs
1 blog
twitter
3 X users
facebook
1 Facebook page

Citations

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40 Dimensions

Readers on

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55 Mendeley
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Title
FragIt: A Tool to Prepare Input Files for Fragment Based Quantum Chemical Calculations
Published in
PLOS ONE, September 2012
DOI 10.1371/journal.pone.0044480
Pubmed ID
Authors

Casper Steinmann, Mikael W. Ibsen, Anne S. Hansen, Jan H. Jensen

Abstract

Near linear scaling fragment based quantum chemical calculations are becoming increasingly popular for treating large systems with high accuracy and is an active field of research. However, it remains difficult to set up these calculations without expert knowledge. To facilitate the use of such methods, software tools need to be available to support these methods and help to set up reasonable input files which will lower the barrier of entry for usage by non-experts. Previous tools relies on specific annotations in structure files for automatic and successful fragmentation such as residues in PDB files. We present a general fragmentation methodology and accompanying tools called FragIt to help setup these calculations. FragIt uses the SMARTS language to locate chemically appropriate fragments in large structures and is applicable to fragmentation of any molecular system given suitable SMARTS patterns. We present SMARTS patterns of fragmentation for proteins, DNA and polysaccharides, specifically for D-galactopyranose for use in cyclodextrins. FragIt is used to prepare input files for the Fragment Molecular Orbital method in the GAMESS program package, but can be extended to other computational methods easily.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 2%
Unknown 54 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 27%
Professor 6 11%
Student > Ph. D. Student 6 11%
Professor > Associate Professor 5 9%
Student > Doctoral Student 4 7%
Other 11 20%
Unknown 8 15%
Readers by discipline Count As %
Chemistry 30 55%
Computer Science 3 5%
Biochemistry, Genetics and Molecular Biology 2 4%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Materials Science 2 4%
Other 5 9%
Unknown 11 20%
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 07 December 2016.
All research outputs
#3,554,828
of 22,665,794 outputs
Outputs from PLOS ONE
#44,009
of 193,511 outputs
Outputs of similar age
#25,487
of 170,555 outputs
Outputs of similar age from PLOS ONE
#739
of 4,261 outputs
Altmetric has tracked 22,665,794 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 193,511 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has done well, scoring higher than 77% 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 170,555 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 85% of its contemporaries.
We're also able to compare this research output to 4,261 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.