Biocellion statistics

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Number of citations per year for the bioinformatics software tool Biocellion
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Biocellion specifications

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Unique identifier OMICS_08774
Name Biocellion
Software type Package/Module
Interface Graphical user interface
Restrictions to use Academic or non-commercial use
Operating system Unix/Linux
Computer skills Medium
Stability Stable
Maintained Yes

Versioning


No version available

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Maintainer


  • person_outline Biocellion

Publications for Biocellion

Biocellion citations

 (7)
library_books

Cell death as a trigger for morphogenesis

2018
PLoS One
PMCID: 5863959
PMID: 29565975
DOI: 10.1371/journal.pone.0191089

[…] We implemented the wrinkle formation model (see ) in Biocellion, an HPC simulation framework designed to accelerate agent-based simulations of biological systems composed of millions to billions of cells. Biocellion, which runs on clusters and has been […]

library_books

PhysiCell: An open source physics based cell simulator for 3 D multicellular systems

2018
PLoS Comput Biol
PMCID: 5841829
PMID: 29474446
DOI: 10.1371/journal.pcbi.1005991

[…] -based simulations of 105 or more cells. However, its complex codebase has many dependencies that can impede participation by new developers; it is only cross-platform compatible by virtual machines. Biocellion [] can simulate billions of cells on cluster computers, but it is closed source, and its restrictive user license has hindered adoption. Timothy was recently developed to simulate large-sca […]

library_books

Modeling de novo granulation of anaerobic sludge

2017
BMC Syst Biol
PMCID: 5514506
PMID: 28716030
DOI: 10.1186/s12918-017-0443-z

[…] sms of enhancing anaerobic granulation, such as addition of positively charged ions and particles of polymers into the UASB system [, ]. To converge granulation model with reactor-like environment, a Biocellion modelling environment can be used [, ]. Possibility to parallelize computation load in Biocellion would eliminate the main bottleneck of the cDynoMics and allow development of a whole react […]

library_books

Exploiting Self organization in Bioengineered Systems: A Computational Approach

2017
Front Bioeng Biotechnol
PMCID: 5408088
PMID: 28503548
DOI: 10.3389/fbioe.2017.00027

[…] ld promise for significant improvements because the vessels could support far more producer cells. Recently, two fast large-scale simulation systems have been developed by Ghaffarizadeh et al. () and Biocellion (Kang et al., ). Both these systems implement an individual-based approach similar to cDynoMiCs employed here. Biocellion is implemented as a distributed architecture executable on the Clou […]

library_books

Comparing individual based approaches to modelling the self organization of multicellular tissues

2017
PLoS Comput Biol
PMCID: 5330541
PMID: 28192427
DOI: 10.1371/journal.pcbi.1005387

[…] r-term challenge is to extend such comparison studies across simulation tools, of which there is an increasing ecosystem, including CompuCell3d [], Morpheus [], EPISIM [], CellSys [], VirtualLeaf [], Biocellion [], BioFVM [], LBIBCell [] and EmbryoMaker []. We emphasize here the lack of ‘benchmarks’ on which to make such comparisons. We propose that the present study offers four examples that coul […]

library_books

Towards Anatomic Scale Agent Based Modeling with a Massively Parallel Spatially Explicit General Purpose Model of Enteric Tissue (SEGMEnT_HPC)

2015
PLoS One
PMCID: 4373890
PMID: 25806784
DOI: 10.1371/journal.pone.0122192

[…] e of agent-agent and agent-local environment interactions can challenge the parallelization of an ABM, and there have been several specialized modeling platforms developed to provide this capability: Biocellion [,], FLAME [,], and Repast HPC [,]. However, despite their advantages in terms of lowering barriers to use and implementation on HPC environments, there are potential limitations on the eff […]


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Biocellion institution(s)
Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA, USA, Department of Computer Science, Utah State University, Logan, UT, USA and Institute for Systems Biology, Seattle, WA, USA

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