The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Virtual Plant Tissue: Building Blocks for Next-Generation Plant Growth Simulation
|
|---|---|
| Published in |
Frontiers in Plant Science, May 2017
|
| DOI | 10.3389/fpls.2017.00686 |
| Pubmed ID | |
| Authors |
Dirk De Vos, Abdiravuf Dzhurakhalov, Sean Stijven, Przemyslaw Klosiewicz, Gerrit T. S. Beemster, Jan Broeckhove |
| Abstract |
Motivation: Computational modeling of plant developmental processes is becoming increasingly important. Cellular resolution plant tissue simulators have been developed, yet they are typically describing physiological processes in an isolated way, strongly delimited in space and time. Results: With plant systems biology moving toward an integrative perspective on development we have built the Virtual Plant Tissue (VPTissue) package to couple functional modules or models in the same framework and across different frameworks. Multiple levels of model integration and coordination enable combining existing and new models from different sources, with diverse options in terms of input/output. Besides the core simulator the toolset also comprises a tissue editor for manipulating tissue geometry and cell, wall, and node attributes in an interactive manner. A parameter exploration tool is available to study parameter dependence of simulation results by distributing calculations over multiple systems. Availability: Virtual Plant Tissue is available as open source (EUPL license) on Bitbucket (https://bitbucket.org/vptissue/vptissue). The project has a website https://vptissue.bitbucket.io. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 33% |
| Switzerland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Chile | 1 | 5% |
| Unknown | 19 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 20% |
| Student > Bachelor | 3 | 15% |
| Student > Ph. D. Student | 3 | 15% |
| Professor | 2 | 10% |
| Student > Master | 2 | 10% |
| Other | 1 | 5% |
| Unknown | 5 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 20% |
| Biochemistry, Genetics and Molecular Biology | 3 | 15% |
| Computer Science | 3 | 15% |
| Engineering | 2 | 10% |
| Nursing and Health Professions | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 5 | 25% |
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 10 June 2017.
All research outputs
#14,717,488
of 23,577,761 outputs
Outputs from Frontiers in Plant Science
#8,661
of 21,628 outputs
Outputs of similar age
#175,197
of 312,175 outputs
Outputs of similar age from Frontiers in Plant Science
#300
of 599 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 21,628 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 55% 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 312,175 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 599 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.