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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Estimating copy numbers of alleles from population-scale high-throughput sequencing data
|
|---|---|
| Published in |
BMC Bioinformatics, January 2015
|
| DOI | 10.1186/1471-2105-16-s1-s4 |
| Pubmed ID | |
| Authors |
Takahiro Mimori, Naoki Nariai, Kaname Kojima, Yukuto Sato, Yosuke Kawai, Yumi Yamaguchi-Kabata, Masao Nagasaki |
| Abstract |
With the recent development of microarray and high-throughput sequencing (HTS) technologies, a number of studies have revealed catalogs of copy number variants (CNVs) and their association with phenotypes and complex traits. In parallel, a number of approaches to predict CNV regions and genotypes are proposed for both microarray and HTS data. However, only a few approaches focus on haplotyping of CNV loci. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 33% |
| Australia | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Norway | 1 | 6% |
| Unknown | 16 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 35% |
| Other | 4 | 24% |
| Student > Ph. D. Student | 3 | 18% |
| Student > Bachelor | 1 | 6% |
| Professor > Associate Professor | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 2 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 29% |
| Computer Science | 3 | 18% |
| Medicine and Dentistry | 2 | 12% |
| Linguistics | 1 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 4 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 25 February 2015.
All research outputs
#15,325,004
of 22,792,160 outputs
Outputs from BMC Bioinformatics
#5,372
of 7,280 outputs
Outputs of similar age
#209,165
of 351,785 outputs
Outputs of similar age from BMC Bioinformatics
#100
of 146 outputs
Altmetric has tracked 22,792,160 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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 351,785 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.