Title |
Cloud-based uniform ChIP-Seq processing tools for modENCODE and ENCODE
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Published in |
BMC Genomics, July 2013
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DOI | 10.1186/1471-2164-14-494 |
Pubmed ID | |
Authors |
Quang M Trinh, Fei-Yang Arthur Jen, Ziru Zhou, Kar Ming Chu, Marc D Perry, Ellen T Kephart, Sergio Contrino, Peter Ruzanov, Lincoln D Stein |
Abstract |
Funded by the National Institutes of Health (NIH), the aim of the Model Organism ENCyclopedia of DNA Elements (modENCODE) project is to provide the biological research community with a comprehensive encyclopedia of functional genomic elements for both model organisms C. elegans (worm) and D. melanogaster (fly). With a total size of just under 10 terabytes of data collected and released to the public, one of the challenges faced by researchers is to extract biologically meaningful knowledge from this large data set. While the basic quality control, pre-processing, and analysis of the data has already been performed by members of the modENCODE consortium, many researchers will wish to reinterpret the data set using modifications and enhancements of the original protocols, or combine modENCODE data with other data sets. Unfortunately this can be a time consuming and logistically challenging proposition. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 2 | 40% |
China | 1 | 20% |
Unknown | 2 | 40% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 40% |
Scientists | 2 | 40% |
Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 2 | 5% |
China | 1 | 2% |
Brazil | 1 | 2% |
Japan | 1 | 2% |
Russia | 1 | 2% |
Unknown | 37 | 86% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 14 | 33% |
Student > Ph. D. Student | 8 | 19% |
Professor > Associate Professor | 7 | 16% |
Student > Master | 6 | 14% |
Professor | 3 | 7% |
Other | 3 | 7% |
Unknown | 2 | 5% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 26 | 60% |
Computer Science | 6 | 14% |
Biochemistry, Genetics and Molecular Biology | 3 | 7% |
Engineering | 2 | 5% |
Sports and Recreations | 1 | 2% |
Other | 3 | 7% |
Unknown | 2 | 5% |