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X Demographics
Mendeley readers
Attention Score in Context
Title |
Identification of yeast cell cycle regulated genes based on genomic features
|
---|---|
Published in |
BMC Systems Biology, July 2013
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DOI | 10.1186/1752-0509-7-70 |
Pubmed ID | |
Authors |
Chao Cheng, Yao Fu, Linsheng Shen, Mark Gerstein |
Abstract |
Time-course microarray experiments have been widely used to identify cell cycle regulated genes. However, the method is not effective for lowly expressed genes and is sensitive to experimental conditions. To complement microarray experiments, we propose a computational method to predict cell cycle regulated genes based on their genomic features - transcription factor binding and motif profiles. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Bolivia, Plurinational State of | 1 | 3% |
Germany | 1 | 3% |
Unknown | 35 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 8 | 22% |
Student > Ph. D. Student | 8 | 22% |
Student > Bachelor | 4 | 11% |
Professor | 4 | 11% |
Student > Master | 4 | 11% |
Other | 5 | 14% |
Unknown | 4 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 15 | 41% |
Biochemistry, Genetics and Molecular Biology | 9 | 24% |
Computer Science | 2 | 5% |
Engineering | 2 | 5% |
Medicine and Dentistry | 2 | 5% |
Other | 2 | 5% |
Unknown | 5 | 14% |
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 30 July 2013.
All research outputs
#21,264,673
of 23,881,329 outputs
Outputs from BMC Systems Biology
#1,006
of 1,126 outputs
Outputs of similar age
#178,674
of 201,008 outputs
Outputs of similar age from BMC Systems Biology
#22
of 22 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,126 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 1st percentile – i.e., 1% 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 201,008 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.