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Attention Score in Context
Title |
Limitations and possibilities of low cell number ChIP-seq
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Published in |
BMC Genomics, November 2012
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DOI | 10.1186/1471-2164-13-645 |
Pubmed ID | |
Authors |
Gregor D Gilfillan, Timothy Hughes, Ying Sheng, Hanne S Hjorthaug, Tobias Straub, Kristina Gervin, Jennifer R Harris, Dag E Undlien, Robert Lyle |
Abstract |
Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-seq) offers high resolution, genome-wide analysis of DNA-protein interactions. However, current standard methods require abundant starting material in the range of 1-20 million cells per immunoprecipitation, and remain a bottleneck to the acquisition of biologically relevant epigenetic data. Using a ChIP-seq protocol optimised for low cell numbers (down to 100,000 cells/IP), we examined the performance of the ChIP-seq technique on a series of decreasing cell numbers. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 293 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 1% |
Germany | 1 | <1% |
Italy | 1 | <1% |
Austria | 1 | <1% |
Sweden | 1 | <1% |
Norway | 1 | <1% |
Canada | 1 | <1% |
United Kingdom | 1 | <1% |
Spain | 1 | <1% |
Other | 1 | <1% |
Unknown | 280 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 93 | 32% |
Researcher | 75 | 26% |
Student > Master | 31 | 11% |
Student > Bachelor | 19 | 6% |
Student > Doctoral Student | 14 | 5% |
Other | 33 | 11% |
Unknown | 28 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 118 | 40% |
Biochemistry, Genetics and Molecular Biology | 96 | 33% |
Medicine and Dentistry | 15 | 5% |
Computer Science | 8 | 3% |
Immunology and Microbiology | 7 | 2% |
Other | 16 | 5% |
Unknown | 33 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 April 2020.
All research outputs
#2,655,917
of 25,374,917 outputs
Outputs from BMC Genomics
#759
of 11,244 outputs
Outputs of similar age
#24,301
of 285,367 outputs
Outputs of similar age from BMC Genomics
#10
of 196 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 285,367 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 196 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.