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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
ChIP-Seq: Library Preparation and Sequencing.
|
|---|---|
| Chapter number | 9 |
| Book title |
Long Non-Coding RNAs
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3378-5_9 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3376-1, 978-1-4939-3378-5
|
| Authors |
Sheaffer, Karyn L, Schug, Jonathan, Karyn L. Sheaffer, Jonathan Schug, Sheaffer, Karyn L. |
| Editors |
Yi Feng, Lin Zhang |
| Abstract |
Chromatin immunoprecipitation with massively parallel DNA sequencing (ChIP-Seq) has been used extensively to determine the genome-wide location of DNA-binding factors, such as transcription factors, posttranscriptionally modified histones, and members of the transcription complex, to assess regulatory input, epigenetic modifications, and transcriptional activity, respectively. Here we describe methods to isolate chromatin from tissues, immunoprecipitate DNA bound to a protein of interest, and perform next-generation sequencing to identify a genome-wide DNA-binding pattern. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 29% |
| India | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 7 | 24% |
| Researcher | 6 | 21% |
| Student > Ph. D. Student | 5 | 17% |
| Student > Master | 4 | 14% |
| Other | 2 | 7% |
| Other | 3 | 10% |
| Unknown | 2 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 55% |
| Agricultural and Biological Sciences | 6 | 21% |
| Neuroscience | 2 | 7% |
| Computer Science | 1 | 3% |
| Medicine and Dentistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 2 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 03 January 2023.
All research outputs
#4,489,217
of 25,089,705 outputs
Outputs from Methods in molecular biology
#1,153
of 14,109 outputs
Outputs of similar age
#70,948
of 405,402 outputs
Outputs of similar age from Methods in molecular biology
#164
of 1,463 outputs
Altmetric has tracked 25,089,705 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,109 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 91% 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 405,402 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 1,463 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.