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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, January 2012
|
| DOI | 10.3389/fninf.2012.00007 |
| Pubmed ID | |
| Authors |
Pierre Bellec, Sébastien Lavoie-Courchesne, Phil Dickinson, Jason P. Lerch, Alex P. Zijdenbos, Alan C. Evans |
| Abstract |
The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output, and cleaned-up files. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available; (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis; (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI). The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 5% |
| Canada | 3 | 3% |
| France | 1 | <1% |
| Cuba | 1 | <1% |
| Finland | 1 | <1% |
| Germany | 1 | <1% |
| Switzerland | 1 | <1% |
| United Kingdom | 1 | <1% |
| China | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 88 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 25 | 24% |
| Student > Ph. D. Student | 19 | 18% |
| Student > Bachelor | 10 | 10% |
| Student > Master | 10 | 10% |
| Student > Doctoral Student | 6 | 6% |
| Other | 18 | 17% |
| Unknown | 16 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 16% |
| Neuroscience | 17 | 16% |
| Engineering | 16 | 15% |
| Computer Science | 14 | 13% |
| Agricultural and Biological Sciences | 7 | 7% |
| Other | 17 | 16% |
| Unknown | 16 | 15% |
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 20 April 2014.
All research outputs
#14,751,888
of 25,123,315 outputs
Outputs from Frontiers in Neuroinformatics
#461
of 819 outputs
Outputs of similar age
#158,257
of 256,075 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#15
of 24 outputs
Altmetric has tracked 25,123,315 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 819 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 42nd percentile – i.e., 42% 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 256,075 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.