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Attention Score in Context
Title |
Computational challenges in the analysis of ancient DNA
|
---|---|
Published in |
Genome Biology, May 2010
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DOI | 10.1186/gb-2010-11-5-r47 |
Pubmed ID | |
Authors |
Kay Prüfer, Udo Stenzel, Michael Hofreiter, Svante Pääbo, Janet Kelso, Richard E Green |
Abstract |
High-throughput sequencing technologies have opened up a new avenue for studying extinct organisms. Here we identify and quantify biases introduced by particular characteristics of ancient DNA samples. These analyses demonstrate the importance of closely related genomic sequence for correctly identifying and classifying bona fide endogenous DNA fragments. We show that more accurate genome divergence estimates from ancient DNA sequence can be attained using at least two outgroup genomes and appropriate filtering. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | 25% |
Unknown | 3 | 75% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 3 | 75% |
Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 266 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 2% |
Germany | 3 | 1% |
United Kingdom | 2 | <1% |
Canada | 2 | <1% |
Turkey | 1 | <1% |
Argentina | 1 | <1% |
Czechia | 1 | <1% |
Russia | 1 | <1% |
Denmark | 1 | <1% |
Other | 2 | <1% |
Unknown | 246 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 75 | 28% |
Researcher | 44 | 17% |
Student > Master | 33 | 12% |
Student > Bachelor | 23 | 9% |
Professor > Associate Professor | 15 | 6% |
Other | 49 | 18% |
Unknown | 27 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 136 | 51% |
Biochemistry, Genetics and Molecular Biology | 54 | 20% |
Arts and Humanities | 13 | 5% |
Computer Science | 7 | 3% |
Social Sciences | 5 | 2% |
Other | 19 | 7% |
Unknown | 32 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 16 December 2023.
All research outputs
#2,567,614
of 25,368,786 outputs
Outputs from Genome Biology
#2,061
of 4,467 outputs
Outputs of similar age
#9,389
of 104,206 outputs
Outputs of similar age from Genome Biology
#7
of 29 outputs
Altmetric has tracked 25,368,786 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 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 53% 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 104,206 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 90% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.