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Recent approaches to the prioritization of candidate disease genes

Overview of attention for article published in Wiley Interdisciplinary Reviews: Systems Biology and Medicine, June 2012
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1 tweeter

Citations

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79 Mendeley
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3 CiteULike
Title
Recent approaches to the prioritization of candidate disease genes
Published in
Wiley Interdisciplinary Reviews: Systems Biology and Medicine, June 2012
DOI 10.1002/wsbm.1177
Pubmed ID
Authors

Doncheva, Nadezhda T., Kacprowski, Tim, Albrecht, Mario

Abstract

Many efforts are still devoted to the discovery of genes involved with specific phenotypes, in particular, diseases. High-throughput techniques are thus applied frequently to detect dozens or even hundreds of candidate genes. However, the experimental validation of many candidates is often an expensive and time-consuming task. Therefore, a great variety of computational approaches has been developed to support the identification of the most promising candidates for follow-up studies. The biomedical knowledge already available about the disease of interest and related genes is commonly exploited to find new gene-disease associations and to prioritize candidates. In this review, we highlight recent methodological advances in this research field of candidate gene prioritization. We focus on approaches that use network information and integrate heterogeneous data sources. Furthermore, we discuss current benchmarking procedures for evaluating and comparing different prioritization methods.

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.

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
Brazil 1 1%
United States 1 1%
Austria 1 1%
Canada 1 1%
Colombia 1 1%
Unknown 73 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 27%
Researcher 20 25%
Student > Master 15 19%
Professor > Associate Professor 6 8%
Student > Doctoral Student 4 5%
Other 13 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 41%
Computer Science 19 24%
Biochemistry, Genetics and Molecular Biology 13 16%
Unspecified 7 9%
Physics and Astronomy 3 4%
Other 5 6%

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 11 June 2012.
All research outputs
#9,962,178
of 12,445,334 outputs
Outputs from Wiley Interdisciplinary Reviews: Systems Biology and Medicine
#227
of 305 outputs
Outputs of similar age
#85,042
of 119,487 outputs
Outputs of similar age from Wiley Interdisciplinary Reviews: Systems Biology and Medicine
#4
of 5 outputs
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So far Altmetric has tracked 305 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
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