Evidence map›Paper›PMID 22936991›Full record

ArticlePloS one2012

BSim: an agent-based tool for modeling bacterial populations in systems and synthetic biology.

Thomas E Gorochowski, Antoni Matyjaszkiewicz, Thomas Todd, Neeraj Oak, Kira Kowalska, Stephen Reid, Krasimira T Tsaneva-Atanasova, Nigel J Savery, Claire S Grierson, Mario di Bernardo

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Simulating ATO Mechanism and EGFR Signaling with Fuzzy Logic and Petri Net.Journal of biomedical physics & engineering · 2021
    Article
  18. Trends in mathematical modeling of host-pathogen interactions.Cellular and molecular life sciences : CMLS · 2020
    Review
  19. Toward Engineering Biosystems With Emergent Collective Functions.Frontiers in bioengineering and biotechnology · 2020
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Thomas E GorochowskiBristol Centre for Complexity Sciences, Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom. thomas.gorochowski@bristol.ac.uk
Antoni Matyjaszkiewicz
Thomas Todd
Neeraj Oak
Kira Kowalska
Stephen Reid
Krasimira T Tsaneva-Atanasova
Nigel J Savery
Claire S Grierson
Mario di Bernardo

Funding

Biotechnology and Biological Sciences Research Council
6 · The paper itself

Abstract

Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher.

Indexed as

Computational BiologyOperonSynthetic BiologySystems Biology

Identifiers

PMID22936991
PMCPMC3427305

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.