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Convert your favorite protein modeling program into a mutation predictor: “MODICT”

Overview of attention for article published in BMC Bioinformatics, October 2016
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Citations

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22 Mendeley
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Title
Convert your favorite protein modeling program into a mutation predictor: “MODICT”
Published in
BMC Bioinformatics, October 2016
DOI 10.1186/s12859-016-1286-0
Pubmed ID
Authors

Ibrahim Tanyalcin, Katrien Stouffs, Dorien Daneels, Carla Al Assaf, Willy Lissens, Anna Jansen, Alexander Gheldof

Abstract

Predict whether a mutation is deleterious based on the custom 3D model of a protein. We have developed MODICT, a mutation prediction tool which is based on per residue RMSD (root mean square deviation) values of superimposed 3D protein models. Our mathematical algorithm was tested for 42 described mutations in multiple genes including renin (REN), beta-tubulin (TUBB2B), biotinidase (BTD), sphingomyelin phosphodiesterase-1 (SMPD1), phenylalanine hydroxylase (PAH) and medium chain Acyl-Coa dehydrogenase (ACADM). Moreover, MODICT scores corresponded to experimentally verified residual enzyme activities in mutated biotinidase, phenylalanine hydroxylase and medium chain Acyl-CoA dehydrogenase. Several commercially available prediction algorithms were tested and results were compared. The MODICT PERL package and the manual can be downloaded from https://github.com/IbrahimTanyalcin/MODICT . We show here that MODICT is capable tool for mutation effect prediction at the protein level, using superimposed 3D protein models instead of sequence based algorithms used by POLYPHEN and SIFT.

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

Geographical breakdown

Country Count As %
Netherlands 1 5%
Unknown 21 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 41%
Researcher 7 32%
Student > Bachelor 2 9%
Student > Doctoral Student 1 5%
Other 1 5%
Other 0 0%
Unknown 2 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 27%
Biochemistry, Genetics and Molecular Biology 5 23%
Computer Science 4 18%
Immunology and Microbiology 2 9%
Chemistry 2 9%
Other 1 5%
Unknown 2 9%
Attention Score in Context

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 11 November 2016.
All research outputs
#14,867,424
of 22,896,955 outputs
Outputs from BMC Bioinformatics
#5,058
of 7,300 outputs
Outputs of similar age
#189,286
of 315,882 outputs
Outputs of similar age from BMC Bioinformatics
#71
of 119 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,300 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 26th percentile – i.e., 26% 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 315,882 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.