Title |
Analysis methods for studying the 3D architecture of the genome
|
---|---|
Published in |
Genome Biology, September 2015
|
DOI | 10.1186/s13059-015-0745-7 |
Pubmed ID | |
Authors |
Ferhat Ay, William S. Noble |
Abstract |
The rapidly increasing quantity of genome-wide chromosome conformation capture data presents great opportunities and challenges in the computational modeling and interpretation of the three-dimensional genome. In particular, with recent trends towards higher-resolution high-throughput chromosome conformation capture (Hi-C) data, the diversity and complexity of biological hypotheses that can be tested necessitates rigorous computational and statistical methods as well as scalable pipelines to interpret these datasets. Here we review computational tools to interpret Hi-C data, including pipelines for mapping, filtering, and normalization, and methods for confidence estimation, domain calling, visualization, and three-dimensional modeling. |
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Canada | 2 | 7% |
United Kingdom | 2 | 7% |
Israel | 1 | 4% |
India | 1 | 4% |
Hungary | 1 | 4% |
Germany | 1 | 4% |
Switzerland | 1 | 4% |
France | 1 | 4% |
Other | 1 | 4% |
Unknown | 9 | 32% |
Demographic breakdown
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---|---|---|
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Members of the public | 13 | 46% |
Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | <1% |
France | 3 | <1% |
Germany | 3 | <1% |
Canada | 3 | <1% |
Japan | 3 | <1% |
Denmark | 3 | <1% |
United Kingdom | 2 | <1% |
Sweden | 2 | <1% |
Spain | 2 | <1% |
Other | 11 | 2% |
Unknown | 480 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 115 | 22% |
Student > Master | 55 | 11% |
Student > Bachelor | 33 | 6% |
Student > Doctoral Student | 26 | 5% |
Other | 69 | 13% |
Unknown | 74 | 14% |
Readers by discipline | Count | As % |
---|---|---|
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Biochemistry, Genetics and Molecular Biology | 167 | 32% |
Computer Science | 46 | 9% |
Mathematics | 13 | 3% |
Medicine and Dentistry | 10 | 2% |
Other | 31 | 6% |
Unknown | 79 | 15% |