Title |
Inherent Signals in Sequencing-Based Chromatin-ImmunoPrecipitation Control Libraries
|
---|---|
Published in |
PLOS ONE, April 2009
|
DOI | 10.1371/journal.pone.0005241 |
Pubmed ID | |
Authors |
Vinsensius B. Vega, Edwin Cheung, Nallasivam Palanisamy, Wing-Kin Sung |
Abstract |
The growth of sequencing-based Chromatin Immuno-Precipitation studies call for a more in-depth understanding of the nature of the technology and of the resultant data to reduce false positives and false negatives. Control libraries are typically constructed to complement such studies in order to mitigate the effect of systematic biases that might be present in the data. In this study, we explored multiple control libraries to obtain better understanding of what they truly represent. |
Mendeley readers
The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | 6% |
Germany | 2 | 2% |
United Kingdom | 2 | 2% |
Italy | 1 | <1% |
Australia | 1 | <1% |
Czechia | 1 | <1% |
Singapore | 1 | <1% |
Canada | 1 | <1% |
Unknown | 97 | 86% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 38 | 34% |
Student > Ph. D. Student | 35 | 31% |
Student > Master | 13 | 12% |
Professor > Associate Professor | 6 | 5% |
Professor | 4 | 4% |
Other | 12 | 11% |
Unknown | 5 | 4% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 77 | 68% |
Biochemistry, Genetics and Molecular Biology | 18 | 16% |
Computer Science | 4 | 4% |
Medicine and Dentistry | 2 | 2% |
Engineering | 2 | 2% |
Other | 4 | 4% |
Unknown | 6 | 5% |