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X Demographics
Mendeley readers
Attention Score in Context
| Title |
NeuroManager: a workflow analysis based simulation management engine for computational neuroscience
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, October 2015
|
| DOI | 10.3389/fninf.2015.00024 |
| Pubmed ID | |
| Authors |
David B. Stockton, Fidel Santamaria |
| Abstract |
We developed NeuroManager, an object-oriented simulation management software engine for computational neuroscience. NeuroManager automates the workflow of simulation job submissions when using heterogeneous computational resources, simulators, and simulation tasks. The object-oriented approach (1) provides flexibility to adapt to a variety of neuroscience simulators, (2) simplifies the use of heterogeneous computational resources, from desktops to super computer clusters, and (3) improves tracking of simulator/simulation evolution. We implemented NeuroManager in MATLAB, a widely used engineering and scientific language, for its signal and image processing tools, prevalence in electrophysiology analysis, and increasing use in college Biology education. To design and develop NeuroManager we analyzed the workflow of simulation submission for a variety of simulators, operating systems, and computational resources, including the handling of input parameters, data, models, results, and analyses. This resulted in 22 stages of simulation submission workflow. The software incorporates progress notification, automatic organization, labeling, and time-stamping of data and results, and integrated access to MATLAB's analysis and visualization tools. NeuroManager provides users with the tools to automate daily tasks, and assists principal investigators in tracking and recreating the evolution of research projects performed by multiple people. Overall, NeuroManager provides the infrastructure needed to improve workflow, manage multiple simultaneous simulations, and maintain provenance of the potentially large amounts of data produced during the course of a research project. |
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 % |
|---|---|---|
| United States | 2 | 40% |
| Switzerland | 2 | 40% |
| Australia | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 33% |
| Student > Bachelor | 4 | 19% |
| Student > Ph. D. Student | 3 | 14% |
| Professor | 1 | 5% |
| Lecturer > Senior Lecturer | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 3 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 24% |
| Agricultural and Biological Sciences | 3 | 14% |
| Engineering | 3 | 14% |
| Neuroscience | 2 | 10% |
| Arts and Humanities | 1 | 5% |
| Other | 4 | 19% |
| Unknown | 3 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 31 December 2015.
All research outputs
#7,432,513
of 23,577,654 outputs
Outputs from Frontiers in Neuroinformatics
#350
of 774 outputs
Outputs of similar age
#90,240
of 280,533 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#3
of 6 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 774 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has gotten more attention than average, scoring higher than 53% of its peers.
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 280,533 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 67% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.