Title |
Recent approaches to the prioritization of candidate disease genes
|
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Published in |
Wiley Interdisciplinary Reviews: Developmental Biology, June 2012
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DOI | 10.1002/wsbm.1177 |
Pubmed ID | |
Authors |
Nadezhda T. Doncheva, Tim Kacprowski, Mario Albrecht |
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. |
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Geographical breakdown
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Colombia | 1 | 1% |
Austria | 1 | 1% |
Brazil | 1 | 1% |
Spain | 1 | 1% |
United States | 1 | 1% |
Unknown | 89 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 22 | 23% |
Researcher | 21 | 22% |
Student > Master | 16 | 17% |
Professor > Associate Professor | 6 | 6% |
Student > Doctoral Student | 4 | 4% |
Other | 13 | 14% |
Unknown | 12 | 13% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 31 | 33% |
Computer Science | 21 | 22% |
Biochemistry, Genetics and Molecular Biology | 12 | 13% |
Medicine and Dentistry | 5 | 5% |
Engineering | 4 | 4% |
Other | 4 | 4% |
Unknown | 17 | 18% |