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X Demographics
Mendeley readers
Attention Score in Context
| Title |
BicSPAM: flexible biclustering using sequential patterns
|
|---|---|
| Published in |
BMC Bioinformatics, May 2014
|
| DOI | 10.1186/1471-2105-15-130 |
| Pubmed ID | |
| Authors |
Rui Henriques, Sara C Madeira |
| Abstract |
Biclustering is a critical task for biomedical applications. Order-preserving biclusters, submatrices where the values of rows induce the same linear ordering across columns, capture local regularities with constant, shifting, scaling and sequential assumptions. Additionally, biclustering approaches relying on pattern mining output deliver exhaustive solutions with an arbitrary number and positioning of biclusters. However, existing order-preserving approaches suffer from robustness, scalability and/or flexibility issues. Additionally, they are not able to discover biclusters with symmetries and parameterizable levels of noise. |
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 % |
|---|---|---|
| Norway | 1 | 50% |
| India | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
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 % |
|---|---|---|
| Portugal | 1 | 3% |
| Brazil | 1 | 3% |
| Unknown | 28 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 7 | 23% |
| Researcher | 6 | 20% |
| Student > Bachelor | 5 | 17% |
| Student > Ph. D. Student | 4 | 13% |
| Professor > Associate Professor | 3 | 10% |
| Other | 2 | 7% |
| Unknown | 3 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 30% |
| Mathematics | 4 | 13% |
| Agricultural and Biological Sciences | 4 | 13% |
| Biochemistry, Genetics and Molecular Biology | 4 | 13% |
| Nursing and Health Professions | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 4 | 13% |
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 24 November 2014.
All research outputs
#12,705,236
of 22,755,127 outputs
Outputs from BMC Bioinformatics
#3,620
of 7,269 outputs
Outputs of similar age
#104,616
of 227,400 outputs
Outputs of similar age from BMC Bioinformatics
#59
of 146 outputs
Altmetric has tracked 22,755,127 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% 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 48th percentile – i.e., 48% 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 227,400 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
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 has gotten more attention than average, scoring higher than 57% of its contemporaries.