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Leveraging protein quaternary structure to identify oncogenic driver mutations

Overview of attention for article published in BMC Bioinformatics, March 2016
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Mentioned by

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4 tweeters

Citations

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7 Dimensions

Readers on

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21 Mendeley
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2 CiteULike
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Title
Leveraging protein quaternary structure to identify oncogenic driver mutations
Published in
BMC Bioinformatics, March 2016
DOI 10.1186/s12859-016-0963-3
Pubmed ID
Authors

Gregory A. Ryslik, Yuwei Cheng, Yorgo Modis, Hongyu Zhao

Abstract

Identifying key "driver" mutations which are responsible for tumorigenesis is critical in the development of new oncology drugs. Due to multiple pharmacological successes in treating cancers that are caused by such driver mutations, a large body of methods have been developed to differentiate these mutations from the benign "passenger" mutations which occur in the tumor but do not further progress the disease. Under the hypothesis that driver mutations tend to cluster in key regions of the protein, the development of algorithms that identify these clusters has become a critical area of research. We have developed a novel methodology, QuartPAC (Quaternary Protein Amino acid Clustering), that identifies non-random mutational clustering while utilizing the protein quaternary structure in 3D space. By integrating the spatial information in the Protein Data Bank (PDB) and the mutational data in the Catalogue of Somatic Mutations in Cancer (COSMIC), QuartPAC is able to identify clusters which are otherwise missed in a variety of proteins. The R package is available on Bioconductor at: http://bioconductor.jp/packages/3.1/bioc/html/QuartPAC.html . QuartPAC provides a unique tool to identify mutational clustering while accounting for the complete folded protein quaternary structure.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 19%
Researcher 4 19%
Student > Doctoral Student 3 14%
Student > Ph. D. Student 3 14%
Professor > Associate Professor 2 10%
Other 2 10%
Unknown 3 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 33%
Computer Science 5 24%
Agricultural and Biological Sciences 2 10%
Immunology and Microbiology 1 5%
Earth and Planetary Sciences 1 5%
Other 2 10%
Unknown 3 14%

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 28 March 2016.
All research outputs
#9,062,787
of 15,466,176 outputs
Outputs from BMC Bioinformatics
#3,457
of 5,648 outputs
Outputs of similar age
#128,719
of 267,076 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 15,466,176 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,648 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one is in the 35th percentile – i.e., 35% 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 267,076 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% 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