Title |
Predicting double-strand DNA breaks using epigenome marks or DNA at kilobase resolution
|
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Published in |
Genome Biology, March 2018
|
DOI | 10.1186/s13059-018-1411-7 |
Pubmed ID | |
Authors |
Raphaël Mourad, Krzysztof Ginalski, Gaëlle Legube, Olivier Cuvier |
Abstract |
Double-strand breaks (DSBs) result from the attack of both DNA strands by multiple sources, including radiation and chemicals. DSBs can cause the abnormal chromosomal rearrangements associated with cancer. Recent techniques allow the genome-wide mapping of DSBs at high resolution, enabling the comprehensive study of their origins. However, these techniques are costly and challenging. Hence, we devise a computational approach to predict DSBs using the epigenomic and chromatin context, for which public data are readily available from the ENCODE project. We achieve excellent prediction accuracy at high resolution. We identify chromatin accessibility, activity, and long-range contacts as the best predictors. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 7 | 15% |
United States | 4 | 8% |
Germany | 4 | 8% |
India | 3 | 6% |
France | 2 | 4% |
Switzerland | 1 | 2% |
Chile | 1 | 2% |
Russia | 1 | 2% |
New Zealand | 1 | 2% |
Other | 6 | 13% |
Unknown | 18 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 30 | 63% |
Scientists | 17 | 35% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 104 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 26 | 25% |
Researcher | 17 | 16% |
Student > Master | 9 | 9% |
Student > Bachelor | 6 | 6% |
Other | 6 | 6% |
Other | 13 | 13% |
Unknown | 27 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 38 | 37% |
Agricultural and Biological Sciences | 19 | 18% |
Medicine and Dentistry | 8 | 8% |
Computer Science | 5 | 5% |
Nursing and Health Professions | 2 | 2% |
Other | 3 | 3% |
Unknown | 29 | 28% |