1. Cell Biology
  2. Computational and Systems Biology

An in silico FSHD muscle fibre for modelling DUX4 dynamics and predicting the impact of therapy

  1. Matthew V Cowley
  2. Johanna Pruller
  3. Massimo Ganassi
  4. Peter S Zammit
  5. Christopher RS Banerji  Is a corresponding author
  1. University of Bath, United Kingdom
  2. King's College London, United Kingdom
  3. The Alan Turing Institute, United Kingdom
https://doi.org/10.7554/eLife.88345
Share this article
Cite this article
  1. Matthew V Cowley
  2. Johanna Pruller
  3. Massimo Ganassi
  4. Peter S Zammit
  5. Christopher RS Banerji
(2023)
An in silico FSHD muscle fibre for modelling DUX4 dynamics and predicting the impact of therapy
eLife 12:e88345.
https://doi.org/10.7554/eLife.88345
  2. Download BibTeX
  3. Download .RIS

Peer review process

This article was accepted for publication via eLife's original publishing model. eLife publishes the authors' accepted manuscript as a PDF only version before the full Version of Record is ready for publication. Peer reviews are published along with the Version of Record.

History

  1. Version of Record published
  2. Accepted Manuscript published
  3. Accepted
  4. Received
  5. Preprint posted

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Matthew V Cowley
  2. Johanna Pruller
  3. Massimo Ganassi
  4. Peter S Zammit
  5. Christopher RS Banerji
(2023)
An in silico FSHD muscle fibre for modelling DUX4 dynamics and predicting the impact of therapy
eLife 12:e88345.
https://doi.org/10.7554/eLife.88345

Share this article

https://doi.org/10.7554/eLife.88345