You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
Attention Score in Context
| Title |
A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array
|
|---|---|
| Published in |
BMC Bioinformatics, May 2007
|
| DOI | 10.1186/1471-2105-8-145 |
| Pubmed ID | |
| Authors |
Tianwei Yu, Hui Ye, Wei Sun, Ker-Chau Li, Zugen Chen, Sharoni Jacobs, Dione K Bailey, David T Wong, Xiaofeng Zhou |
| Abstract |
DNA copy number aberration (CNA) is one of the key characteristics of cancer cells. Recent studies demonstrated the feasibility of utilizing high density single nucleotide polymorphism (SNP) genotyping arrays to detect CNA. Compared with the two-color array-based comparative genomic hybridization (array-CGH), the SNP arrays offer much higher probe density and lower signal-to-noise ratio at the single SNP level. To accurately identify small segments of CNA from SNP array data, segmentation methods that are sensitive to CNA while resistant to noise are required. |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 7% |
| Malaysia | 1 | 3% |
| Germany | 1 | 3% |
| Norway | 1 | 3% |
| Unknown | 25 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 40% |
| Professor > Associate Professor | 5 | 17% |
| Student > Ph. D. Student | 5 | 17% |
| Student > Bachelor | 4 | 13% |
| Unspecified | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 63% |
| Computer Science | 3 | 10% |
| Mathematics | 3 | 10% |
| Engineering | 2 | 7% |
| Energy | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 1 | 3% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 18 November 2010.
All research outputs
#12,846,160
of 22,649,029 outputs
Outputs from BMC Bioinformatics
#3,776
of 7,234 outputs
Outputs of similar age
#60,291
of 72,064 outputs
Outputs of similar age from BMC Bioinformatics
#32
of 40 outputs
Altmetric has tracked 22,649,029 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,234 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 45th percentile – i.e., 45% 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 72,064 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.