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Realizing drug repositioning by adapting a recommendation system to handle the process

Overview of attention for article published in BMC Bioinformatics, April 2018
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Mentioned by

twitter
2 tweeters

Citations

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19 Dimensions

Readers on

mendeley
30 Mendeley
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1 CiteULike
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Title
Realizing drug repositioning by adapting a recommendation system to handle the process
Published in
BMC Bioinformatics, April 2018
DOI 10.1186/s12859-018-2142-1
Pubmed ID
Authors

Makbule Guclin Ozsoy, Tansel Özyer, Faruk Polat, Reda Alhajj

Abstract

Drug repositioning is the process of identifying new targets for known drugs. It can be used to overcome problems associated with traditional drug discovery by adapting existing drugs to treat new discovered diseases. Thus, it may reduce associated risk, cost and time required to identify and verify new drugs. Nowadays, drug repositioning has received more attention from industry and academia. To tackle this problem, researchers have applied many different computational methods and have used various features of drugs and diseases. In this study, we contribute to the ongoing research efforts by combining multiple features, namely chemical structures, protein interactions and side-effects to predict new indications of target drugs. To achieve our target, we realize drug repositioning as a recommendation process and this leads to a new perspective in tackling the problem. The utilized recommendation method is based on Pareto dominance and collaborative filtering. It can also integrate multiple data-sources and multiple features. For the computation part, we applied several settings and we compared their performance. Evaluation results show that the proposed method can achieve more concentrated predictions with high precision, where nearly half of the predictions are true. Compared to other state of the art methods described in the literature, the proposed method is better at making right predictions by having higher precision. The reported results demonstrate the applicability and effectiveness of recommendation methods for drug repositioning.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 17%
Lecturer 3 10%
Student > Doctoral Student 3 10%
Researcher 3 10%
Student > Bachelor 2 7%
Other 3 10%
Unknown 11 37%
Readers by discipline Count As %
Computer Science 6 20%
Biochemistry, Genetics and Molecular Biology 5 17%
Business, Management and Accounting 3 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Agricultural and Biological Sciences 1 3%
Other 3 10%
Unknown 11 37%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 16 April 2018.
All research outputs
#10,225,854
of 12,808,036 outputs
Outputs from BMC Bioinformatics
#3,937
of 4,757 outputs
Outputs of similar age
#203,806
of 271,507 outputs
Outputs of similar age from BMC Bioinformatics
#11
of 24 outputs
Altmetric has tracked 12,808,036 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,757 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 7th percentile – i.e., 7% 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 271,507 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.