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An in silico FSHD muscle fibre for modelling DUX4 dynamics and predicting the impact of therapy
Matthew V. Cowley, Johanna Pruller, Massimo Ganassi, Peter S. Zammit, Christopher R. S. Banerji
doi: https://doi.org/10.1101/2022.12.12.520053
Matthew V. Cowley
1Centre for Sustainable and Circular Technologies, Department of Chemistry, University of Bath, Claverton Down, Bath BA2 7AY, UK
Johanna Pruller
2King’s College London, Randall Centre for Cell and Molecular Biophysics, New Hunt’s House, Guy’s Campus, London SE1 1UL, UK
Massimo Ganassi
2King’s College London, Randall Centre for Cell and Molecular Biophysics, New Hunt’s House, Guy’s Campus, London SE1 1UL, UK
Peter S. Zammit
2King’s College London, Randall Centre for Cell and Molecular Biophysics, New Hunt’s House, Guy’s Campus, London SE1 1UL, UK
Christopher R. S. Banerji
2King’s College London, Randall Centre for Cell and Molecular Biophysics, New Hunt’s House, Guy’s Campus, London SE1 1UL, UK
3The Alan Turing Institute, British Library, 96 Euston Rd, London NW1 2DB, UK
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Posted December 12, 2022.
An in silico FSHD muscle fibre for modelling DUX4 dynamics and predicting the impact of therapy
Matthew V. Cowley, Johanna Pruller, Massimo Ganassi, Peter S. Zammit, Christopher R. S. Banerji
bioRxiv 2022.12.12.520053; doi: https://doi.org/10.1101/2022.12.12.520053
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