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Mendeley readers
Attention Score in Context
| Title |
In silico molecular cytogenetics: a bioinformatic approach to prioritization of candidate genes and copy number variations for basic and clinical genome research
|
|---|---|
| Published in |
Molecular Cytogenetics, December 2014
|
| DOI | 10.1186/s13039-014-0098-z |
| Pubmed ID | |
| Authors |
Ivan Y Iourov, Svetlana G Vorsanova, Yuri B Yurov |
| Abstract |
The availability of multiple in silico tools for prioritizing genetic variants widens the possibilities for converting genomic data into biological knowledge. However, in molecular cytogenetics, bioinformatic analyses are generally limited to result visualization or database mining for finding similar cytogenetic data. Obviously, the potential of bioinformatics might go beyond these applications. On the other hand, the requirements for performing successful in silico analyses (i.e. deep knowledge of computer science, statistics etc.) can hinder the implementation of bioinformatics in clinical and basic molecular cytogenetic research. Here, we propose a bioinformatic approach to prioritization of genomic variations that is able to solve these problems. |
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 % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 3% |
| Unknown | 38 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 28% |
| Student > Doctoral Student | 4 | 10% |
| Researcher | 4 | 10% |
| Student > Postgraduate | 4 | 10% |
| Student > Master | 3 | 8% |
| Other | 5 | 13% |
| Unknown | 8 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 31% |
| Biochemistry, Genetics and Molecular Biology | 10 | 26% |
| Medicine and Dentistry | 4 | 10% |
| Computer Science | 3 | 8% |
| Neuroscience | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 6 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 20 December 2014.
All research outputs
#14,206,722
of 22,774,233 outputs
Outputs from Molecular Cytogenetics
#117
of 400 outputs
Outputs of similar age
#191,589
of 361,040 outputs
Outputs of similar age from Molecular Cytogenetics
#7
of 24 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 400 research outputs from this source. They receive a mean Attention Score of 2.4. This one has gotten more attention than average, scoring higher than 68% 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 361,040 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.