| Title |
Incorporating phylogenetic-based covarying mutations into RNAalifold for RNA consensus structure prediction
|
|---|---|
| Published in |
BMC Bioinformatics, April 2013
|
| DOI | 10.1186/1471-2105-14-142 |
| Pubmed ID | |
| Authors |
Ping Ge, Shaojie Zhang |
| Abstract |
RNAalifold, a popular computational method for RNA consensus structure prediction, incorporates covarying mutations into a thermodynamic model to fold the aligned RNA sequences. When quantifying covariance, it evaluates conserved signals of two aligned columns with base-pairing rules. This scoring scheme performs better than some other approaches, such as mutual information. However it ignores the phylogenetic history of the aligned sequences, which is an important criterion to evaluate the level of sequence covariance. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 25% |
| France | 1 | 25% |
| Norway | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Iran, Islamic Republic of | 1 | 4% |
| United States | 1 | 4% |
| France | 1 | 4% |
| Unknown | 25 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 29% |
| Student > Ph. D. Student | 8 | 29% |
| Student > Master | 4 | 14% |
| Student > Doctoral Student | 2 | 7% |
| Professor > Associate Professor | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 2 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 46% |
| Biochemistry, Genetics and Molecular Biology | 6 | 21% |
| Computer Science | 4 | 14% |
| Mathematics | 1 | 4% |
| Engineering | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 3 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 29 April 2013.
All research outputs
#13,687,464
of 22,708,120 outputs
Outputs from BMC Bioinformatics
#4,440
of 7,256 outputs
Outputs of similar age
#105,226
of 193,472 outputs
Outputs of similar age from BMC Bioinformatics
#77
of 123 outputs
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