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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions
|
|---|---|
| Published in |
Frontiers in Microbiology, February 2018
|
| DOI | 10.3389/fmicb.2018.00033 |
| Pubmed ID | |
| Authors |
Jared L. Wilmoth, Peter W. Doak, Andrea Timm, Michelle Halsted, John D. Anderson, Marta Ginovart, Clara Prats, Xavier Portell, Scott T. Retterer, Miguel Fuentes-Cabrera |
| Abstract |
The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants ofP.aeruginosaunder spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 65 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 37% |
| Researcher | 11 | 17% |
| Student > Doctoral Student | 4 | 6% |
| Professor | 3 | 5% |
| Student > Master | 3 | 5% |
| Other | 6 | 9% |
| Unknown | 14 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 20% |
| Agricultural and Biological Sciences | 10 | 15% |
| Engineering | 6 | 9% |
| Environmental Science | 4 | 6% |
| Chemical Engineering | 4 | 6% |
| Other | 10 | 15% |
| Unknown | 18 | 28% |
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 07 February 2018.
All research outputs
#14,374,920
of 23,020,670 outputs
Outputs from Frontiers in Microbiology
#12,563
of 25,142 outputs
Outputs of similar age
#239,132
of 437,329 outputs
Outputs of similar age from Frontiers in Microbiology
#315
of 513 outputs
Altmetric has tracked 23,020,670 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 25,142 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 45th percentile – i.e., 45% 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 437,329 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 513 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.