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X Demographics
Mendeley readers
Attention Score in Context
| Title |
VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces
|
|---|---|
| Published in |
BMC Bioinformatics, February 2017
|
| DOI | 10.1186/s12859-017-1505-3 |
| Pubmed ID | |
| Authors |
Raja H. Ali, Mikael Bark, Jorge Miró, Sayyed A. Muhammad, Joel Sjöstrand, Syed M. Zubair, Raja M. Abbas, Lars Arvestad |
| Abstract |
MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical difficulties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e.g., convergence, mixing and interactive exploration of both continuous and tree parameters. We have written a software called VMCMC to simplify post-processing of MCMC traces with, for example, automatic burn-in estimation. VMCMC can also be used both as a GUI-based application, supporting interactive exploration, and as a command-line tool suitable for automated pipelines. VMCMC is a free software available under the New BSD License. Executable jar files, tutorial manual and source code can be downloaded from https://bitbucket.org/rhali/visualmcmc/ . |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Venezuela, Bolivarian Republic of | 1 | 20% |
| Sao Tome and Principe | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 24% |
| Student > Ph. D. Student | 5 | 20% |
| Student > Bachelor | 4 | 16% |
| Researcher | 4 | 16% |
| Lecturer > Senior Lecturer | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 2 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 36% |
| Biochemistry, Genetics and Molecular Biology | 4 | 16% |
| Computer Science | 4 | 16% |
| Mathematics | 2 | 8% |
| Veterinary Science and Veterinary Medicine | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 2 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 28 November 2020.
All research outputs
#14,507,233
of 25,734,859 outputs
Outputs from BMC Bioinformatics
#3,869
of 7,739 outputs
Outputs of similar age
#211,227
of 429,564 outputs
Outputs of similar age from BMC Bioinformatics
#63
of 150 outputs
Altmetric has tracked 25,734,859 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,739 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 49th percentile – i.e., 49% 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 429,564 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.