Title |
Atlas2 Cloud: a framework for personal genome analysis in the cloud
|
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Published in |
BMC Genomics, October 2012
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DOI | 10.1186/1471-2164-13-s6-s19 |
Pubmed ID | |
Authors |
Uday S Evani, Danny Challis, Jin Yu, Andrew R Jackson, Sameer Paithankar, Matthew N Bainbridge, Adinarayana Jakkamsetti, Peter Pham, Cristian Coarfa, Aleksandar Milosavljevic, Fuli Yu |
Abstract |
Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 4% |
Brazil | 1 | 1% |
France | 1 | 1% |
China | 1 | 1% |
Sweden | 1 | 1% |
Unknown | 61 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 27 | 40% |
Student > Ph. D. Student | 15 | 22% |
Other | 7 | 10% |
Student > Master | 6 | 9% |
Student > Bachelor | 5 | 7% |
Other | 8 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 31 | 46% |
Biochemistry, Genetics and Molecular Biology | 13 | 19% |
Computer Science | 9 | 13% |
Medicine and Dentistry | 6 | 9% |
Engineering | 4 | 6% |
Other | 2 | 3% |
Unknown | 3 | 4% |