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Attention Score in Context
Title |
Mining differential top-k co-expression patterns from time course comparative gene expression datasets
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Published in |
BMC Bioinformatics, July 2013
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DOI | 10.1186/1471-2105-14-230 |
Pubmed ID | |
Authors |
Yu-Cheng Liu, Chun-Pei Cheng, Vincent S Tseng |
Abstract |
Frequent pattern mining analysis applied on microarray dataset appears to be a promising strategy for identifying relationships between gene expression levels. Unfortunately, too many itemsets (co-expressed genes) are identified by this analysis method since it does not consider the importance of each gene within biological processes to a cellular response and does not take into account temporal properties under biological treatment-control matched conditions in a microarray dataset. |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 3% |
Netherlands | 1 | 3% |
Belgium | 1 | 3% |
Unknown | 32 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 31% |
Researcher | 8 | 23% |
Professor | 4 | 11% |
Student > Master | 4 | 11% |
Lecturer | 2 | 6% |
Other | 4 | 11% |
Unknown | 2 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 16 | 46% |
Agricultural and Biological Sciences | 8 | 23% |
Biochemistry, Genetics and Molecular Biology | 4 | 11% |
Mathematics | 1 | 3% |
Unspecified | 1 | 3% |
Other | 1 | 3% |
Unknown | 4 | 11% |
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 23 July 2013.
All research outputs
#15,274,524
of 22,714,025 outputs
Outputs from BMC Bioinformatics
#5,365
of 7,260 outputs
Outputs of similar age
#121,908
of 197,439 outputs
Outputs of similar age from BMC Bioinformatics
#69
of 94 outputs
Altmetric has tracked 22,714,025 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 7,260 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 197,439 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 94 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.