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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MetaSel: a metaphase selection tool using a Gaussian-based classification technique
|
|---|---|
| Published in |
BMC Bioinformatics, October 2013
|
| DOI | 10.1186/1471-2105-14-s16-s13 |
| Pubmed ID | |
| Authors |
Ravi Uttamatanin, Peerapol Yuvapoositanon, Apichart Intarapanich, Saowaluck Kaewkamnerd, Ratsapan Phuksaritanon, Anunchai Assawamakin, Sissades Tongsima |
| Abstract |
Identification of good metaphase spreads is an important step in chromosome analysis for identifying individuals with genetic disorders. The process of finding suitable metaphase chromosomes for accurate clinical analysis is, however, very time consuming since they are selected manually. The selection of suitable metaphase chromosome spreads thus represents a major bottleneck for conventional cytogenetic analysis. Although many algorithms have been developed for karyotyping, none have adequately addressed the critical bottleneck of selecting suitable chromosome spreads. In this paper, we present a software tool that uses a simple rule-based system to efficiently identify metaphase spreads suitable for karyotyping. |
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 % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 6 | 23% |
| Student > Master | 4 | 15% |
| Student > Ph. D. Student | 3 | 12% |
| Student > Doctoral Student | 2 | 8% |
| Other | 1 | 4% |
| Other | 5 | 19% |
| Unknown | 5 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 7 | 27% |
| Agricultural and Biological Sciences | 5 | 19% |
| Computer Science | 4 | 15% |
| Biochemistry, Genetics and Molecular Biology | 3 | 12% |
| Medicine and Dentistry | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 5 | 19% |
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 27 January 2015.
All research outputs
#17,719,891
of 22,754,104 outputs
Outputs from BMC Bioinformatics
#5,924
of 7,269 outputs
Outputs of similar age
#151,630
of 212,102 outputs
Outputs of similar age from BMC Bioinformatics
#86
of 116 outputs
Altmetric has tracked 22,754,104 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,269 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 13th percentile – i.e., 13% 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 212,102 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 116 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.