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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An estimation method for inference of gene regulatory net-work using Bayesian network with uniting of partial problems
|
|---|---|
| Published in |
BMC Genomics, January 2012
|
| DOI | 10.1186/1471-2164-13-s1-s12 |
| Pubmed ID | |
| Authors |
Yukito Watanabe, Shigeto Seno, Yoichi Takenaka, Hideo Matsuda |
| Abstract |
Bayesian networks (BNs) have been widely used to estimate gene regulatory networks. Many BN methods have been developed to estimate networks from microarray data. However, two serious problems reduce the effectiveness of current BN methods. The first problem is that BN-based methods require huge computational time to estimate large-scale networks. The second is that the estimated network cannot have cyclic structures, even if the actual network has such structures. |
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 % |
|---|---|---|
| Japan | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 4% |
| Unknown | 26 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 30% |
| Student > Master | 7 | 26% |
| Student > Ph. D. Student | 6 | 22% |
| Professor > Associate Professor | 3 | 11% |
| Professor | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 37% |
| Agricultural and Biological Sciences | 5 | 19% |
| Engineering | 4 | 15% |
| Biochemistry, Genetics and Molecular Biology | 3 | 11% |
| Environmental Science | 1 | 4% |
| Other | 3 | 11% |
| Unknown | 1 | 4% |
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 20 May 2012.
All research outputs
#17,286,379
of 25,374,917 outputs
Outputs from BMC Genomics
#7,120
of 11,244 outputs
Outputs of similar age
#171,692
of 251,196 outputs
Outputs of similar age from BMC Genomics
#69
of 118 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.