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Mendeley readers
Attention Score in Context
Chapter title |
Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning.
|
---|---|
Chapter number | 23 |
Book title |
Data Mining Techniques for the Life Sciences
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3572-7_23 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3570-3, 978-1-4939-3572-7
|
Authors |
Salvatore Alaimo, Rosalba Giugno, Alfredo Pulvirenti |
Editors |
Oliviero Carugo, Frank Eisenhaber |
Abstract |
The usage of computational methods in drug discovery is a common practice. More recently, by exploiting the wealth of biological knowledge bases, a novel approach called drug repositioning has raised. Several computational methods are available, and these try to make a high-level integration of all the knowledge in order to discover unknown mechanisms. In this chapter, we review drug-target interaction prediction methods based on a recommendation system. We also give some extensions which go beyond the bipartite network case. |
Twitter Demographics
The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 8 | 22% |
Researcher | 6 | 16% |
Student > Master | 4 | 11% |
Lecturer | 2 | 5% |
Other | 2 | 5% |
Other | 5 | 14% |
Unknown | 10 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 8 | 22% |
Engineering | 3 | 8% |
Agricultural and Biological Sciences | 3 | 8% |
Biochemistry, Genetics and Molecular Biology | 2 | 5% |
Medicine and Dentistry | 2 | 5% |
Other | 6 | 16% |
Unknown | 13 | 35% |
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 31 January 2017.
All research outputs
#18,463,662
of 22,877,793 outputs
Outputs from Methods in molecular biology
#7,924
of 13,131 outputs
Outputs of similar age
#284,559
of 393,697 outputs
Outputs of similar age from Methods in molecular biology
#845
of 1,471 outputs
Altmetric has tracked 22,877,793 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 13,131 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,471 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.