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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An improved sequence based prediction protocol for DNA-binding proteins using SVM and comprehensive feature analysis
|
|---|---|
| Published in |
BMC Bioinformatics, March 2013
|
| DOI | 10.1186/1471-2105-14-90 |
| Pubmed ID | |
| Authors |
Chuanxin Zou, Jiayu Gong, Honglin Li |
| Abstract |
DNA-binding proteins (DNA-BPs) play a pivotal role in both eukaryotic and prokaryotic proteomes. There have been several computational methods proposed in the literature to deal with the DNA-BPs, many informative features and properties were used and proved to have significant impact on this problem. However the ultimate goal of Bioinformatics is to be able to predict the DNA-BPs directly from primary sequence. |
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 % |
|---|---|---|
| Norway | 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 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| Germany | 1 | 1% |
| Israel | 1 | 1% |
| Iran, Islamic Republic of | 1 | 1% |
| Russia | 1 | 1% |
| Spain | 1 | 1% |
| Unknown | 69 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 14% |
| Researcher | 11 | 14% |
| Professor > Associate Professor | 9 | 12% |
| Student > Master | 8 | 11% |
| Student > Bachelor | 5 | 7% |
| Other | 15 | 20% |
| Unknown | 17 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 22 | 29% |
| Agricultural and Biological Sciences | 13 | 17% |
| Biochemistry, Genetics and Molecular Biology | 6 | 8% |
| Engineering | 6 | 8% |
| Unspecified | 5 | 7% |
| Other | 6 | 8% |
| Unknown | 18 | 24% |
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 09 March 2013.
All research outputs
#20,185,720
of 22,701,287 outputs
Outputs from BMC Bioinformatics
#6,827
of 7,254 outputs
Outputs of similar age
#171,531
of 195,385 outputs
Outputs of similar age from BMC Bioinformatics
#137
of 143 outputs
Altmetric has tracked 22,701,287 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 7,254 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 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 195,385 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 143 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.