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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Copy number variation detection using next generation sequencing read counts
|
|---|---|
| Published in |
BMC Bioinformatics, April 2014
|
| DOI | 10.1186/1471-2105-15-109 |
| Pubmed ID | |
| Authors |
Heng Wang, Dan Nettleton, Kai Ying |
| Abstract |
A copy number variation (CNV) is a difference between genotypes in the number of copies of a genomic region. Next generation sequencing (NGS) technologies provide sensitive and accurate tools for detecting genomic variations that include CNVs. However, statistical approaches for CNV identification using NGS are limited. We propose a new methodology for detecting CNVs using NGS data. This method (henceforth denoted by m-HMM) is based on a hidden Markov model with emission probabilities that are governed by mixture distributions. We use the Expectation-Maximization (EM) algorithm to estimate the parameters in the model. |
X Demographics
The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 18% |
| Italy | 1 | 6% |
| United Kingdom | 1 | 6% |
| India | 1 | 6% |
| Germany | 1 | 6% |
| France | 1 | 6% |
| Norway | 1 | 6% |
| Mexico | 1 | 6% |
| Canada | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 5 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 53% |
| Members of the public | 8 | 47% |
Mendeley readers
The data shown below were compiled from readership statistics for 215 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 3 | 1% |
| United Kingdom | 3 | 1% |
| Norway | 2 | <1% |
| United States | 2 | <1% |
| Uruguay | 1 | <1% |
| Brazil | 1 | <1% |
| Sweden | 1 | <1% |
| South Africa | 1 | <1% |
| Germany | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 196 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 63 | 29% |
| Researcher | 48 | 22% |
| Student > Master | 26 | 12% |
| Student > Bachelor | 16 | 7% |
| Student > Postgraduate | 12 | 6% |
| Other | 34 | 16% |
| Unknown | 16 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 106 | 49% |
| Biochemistry, Genetics and Molecular Biology | 42 | 20% |
| Computer Science | 19 | 9% |
| Medicine and Dentistry | 15 | 7% |
| Engineering | 4 | 2% |
| Other | 11 | 5% |
| Unknown | 18 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 23 December 2021.
All research outputs
#2,107,336
of 23,975,876 outputs
Outputs from BMC Bioinformatics
#526
of 7,474 outputs
Outputs of similar age
#21,865
of 230,093 outputs
Outputs of similar age from BMC Bioinformatics
#10
of 125 outputs
Altmetric has tracked 23,975,876 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,474 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 92% 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 230,093 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 125 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 92% of its contemporaries.