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Open Source Science

https://github.com/aresio/procell

Stochastic simulation of cell populations proliferation

https://github.com/aresio/procell

Science Score: 33.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ✓
    Academic publication links
    Links to: ieee.org
  • ✓
    Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (9.4%) to scientific vocabulary

Keywords

cells modeling proliferation simulation stochastic
Last synced: 5 months ago · JSON representation

Repository

Stochastic simulation of cell populations proliferation

Basic Info
  • Host: GitHub
  • Owner: aresio
  • License: gpl-2.0
  • Language: Python
  • Default Branch: master
  • Size: 1.25 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 1
Topics
cells modeling proliferation simulation stochastic
Created about 8 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

ProCell

ProCell is an award winning modeling and simulation framework designed to investigate cell proliferation dynamics that, differently from other approaches, takes into account the inherent stochasticity of cell division events.

ProCell manipulates raw data coming from flow cytometry experiments. Specifically, uses as input: - a histogram of initial cell fluorescences (e.g., GFP signal in the population); - the number of different sub-populations, along with their proportions; - the mean and standard deviation of division time for each population; - a fluorescence minimum threshold; - a maximum simulation time T, expressed in hours.

The output produced by ProCell is a histogram of GFP fluorescence after time T.

Installing and using ProCell

ProCell can be easily installed with pip:

pip install procell

Once installed, ProCell's new GUI designed by Luca Zanini can be launched by typing:

python -m procell.gui

from the console.

A tutorial about modeling, calibration, simulation and validation will be published soon.

You can find a list of ProCell's pre-requisites here:

https://docs.google.com/document/d/1OC0DDQQHAKs6sMOi7hWleWcwgU04h9RAsZzOye6dnAU/edit?usp=sharing

GPU version of ProCell

cuProCell is a CUDA-accelerated version of ProCell, able to strongly reduce the computational effort of simulations. The GPU implementation is provided as subpackage in this repository. Further information can be found at: https://github.com/ericniso/cuda-pro-cell

More info about ProCell

If you need additional information about ProCell please write to: nobile@disco.unimib.it.

Citing ProCell

Nobile M.S., Vlachou T., Spolaor S., Bossi D., Cazzaniga P., Lanfrancone L., Mauri G., Pelicci P.G., Besozzi D.: Modeling cell proliferation in human acute myeloid leukemia xenografts, Bioinformatics, 35(18):3378-3386, 2019

Nobile M.S., Vlachou T., Spolaor S., Cazzaniga P., Mauri G., Pelicci P.G., Besozzi D.: ProCell: Investigating cell proliferation with Swarm Intelligence, Proceedings of the 16th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2019), Certosa di Pontignano, Siena, Tuscany, Italy, 2019

Nobile M.S., Nisoli E., Vlachou T., Spolaor S., Cazzaniga P., Mauri G., Pelicci P.G., Besozzi D.: cuProCell: GPU-accelerated analysis of cellproliferation with flow cytometry data, IEEE Journal of Biomedical and Health Informatics, 2020 (in press)

Owner

  • Name: Marco S. Nobile
  • Login: aresio
  • Kind: user
  • Location: Venice, Italy
  • Company: Ca' Foscari University

I have a BS, MS and Ph.D. in Computer Science. I am a Associate Professor at the Ca' Foscari University of Venice

GitHub Events

Total
Last Year

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 72
  • Total Committers: 2
  • Avg Commits per committer: 36.0
  • Development Distribution Score (DDS): 0.278
Top Committers
Name Email Commits
Marco S. Nobile n****e@d****t 52
Nobile m****e@t****l 20
Committer Domains (Top 20 + Academic)
tue.nl: 1 disco.unimib.it: 1

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • pypi 4 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 10
  • Total maintainers: 1
pypi.org: procell

ProCell - cell proliferation framework

  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 4 Last month
Rankings
Dependent packages count: 10.1%
Dependent repos count: 21.6%
Forks count: 22.7%
Average: 32.3%
Stargazers count: 38.8%
Downloads: 68.4%
Maintainers (1)
aresio
Last synced: 6 months ago

Dependencies

setup.py pypi
  • fst-pso *
  • matplotlib *
  • miniful *
  • numpy *
  • pandas *
  • simpful *