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Improving protein fold recognition using the amalgamation of evolutionary-based and structural based information

Overview of attention for article published in BMC Bioinformatics, December 2014
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Title
Improving protein fold recognition using the amalgamation of evolutionary-based and structural based information
Published in
BMC Bioinformatics, December 2014
DOI 10.1186/1471-2105-15-s16-s12
Pubmed ID
Authors

Kuldip K Paliwal, Alok Sharma, James Lyons, Abdollah Dehzangi

Abstract

Deciphering three dimensional structure of a protein sequence is a challenging task in biological science. Protein fold recognition and protein secondary structure prediction are transitional steps in identifying the three dimensional structure of a protein. For protein fold recognition, evolutionary-based information of amino acid sequences from the position specific scoring matrix (PSSM) has been recently applied with improved results. On the other hand, the SPINE-X predictor has been developed and applied for protein secondary structure prediction. Several reported methods for protein fold recognition have only limited accuracy. In this paper, we have developed a strategy of combining evolutionary-based information (from PSSM) and predicted secondary structure using SPINE-X to improve protein fold recognition. The strategy is based on finding the probabilities of amino acid pairs (AAP). The proposed method has been tested on several protein benchmark datasets and an improvement of 8.9% recognition accuracy has been achieved. We have achieved, for the first time over 90% and 75% prediction accuracies for sequence similarity values below 40% and 25%, respectively. We also obtain 90.6% and 77.0% prediction accuracies, respectively, for the Extended Ding and Dubchak and Taguchi and Gromiha benchmark protein fold recognition datasets widely used for in the literature.

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The data shown below were collected from the profile of 1 X user 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Israel 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 27%
Student > Postgraduate 4 15%
Researcher 3 12%
Student > Bachelor 2 8%
Student > Master 2 8%
Other 3 12%
Unknown 5 19%
Readers by discipline Count As %
Computer Science 6 23%
Biochemistry, Genetics and Molecular Biology 5 19%
Agricultural and Biological Sciences 5 19%
Medicine and Dentistry 3 12%
Unspecified 1 4%
Other 1 4%
Unknown 5 19%
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 10 February 2015.
All research outputs
#14,800,211
of 22,787,797 outputs
Outputs from BMC Bioinformatics
#5,038
of 7,279 outputs
Outputs of similar age
#202,874
of 360,857 outputs
Outputs of similar age from BMC Bioinformatics
#90
of 138 outputs
Altmetric has tracked 22,787,797 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,279 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 360,857 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.