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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Trends in Programming Languages for Neuroscience Simulations
|
|---|---|
| Published in |
Frontiers in Neuroscience, December 2009
|
| DOI | 10.3389/neuro.01.036.2009 |
| Pubmed ID | |
| Authors |
Andrew P. Davison, Michael L. Hines, Eilif Muller |
| Abstract |
Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing. |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 5% |
| United Kingdom | 4 | 3% |
| Germany | 3 | 2% |
| Canada | 3 | 2% |
| Switzerland | 2 | 2% |
| France | 2 | 2% |
| New Zealand | 1 | <1% |
| India | 1 | <1% |
| Japan | 1 | <1% |
| Other | 3 | 2% |
| Unknown | 104 | 80% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 36 | 28% |
| Student > Ph. D. Student | 25 | 19% |
| Student > Master | 16 | 12% |
| Student > Bachelor | 10 | 8% |
| Professor | 8 | 6% |
| Other | 25 | 19% |
| Unknown | 10 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 36 | 28% |
| Computer Science | 29 | 22% |
| Engineering | 18 | 14% |
| Neuroscience | 11 | 8% |
| Psychology | 8 | 6% |
| Other | 16 | 12% |
| Unknown | 12 | 9% |
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 09 December 2021.
All research outputs
#13,358,992
of 22,660,862 outputs
Outputs from Frontiers in Neuroscience
#5,686
of 9,807 outputs
Outputs of similar age
#129,602
of 163,831 outputs
Outputs of similar age from Frontiers in Neuroscience
#23
of 34 outputs
Altmetric has tracked 22,660,862 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,807 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one is in the 40th percentile – i.e., 40% 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 163,831 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.