The influence of methylation status on a stochastic model of MGMT dynamics in glioblastoma: phenotypic selection can occur with and without a downshift in promoter methylation status

DOI10.1016/J.JTBI.2021.110662zbMath1465.92029OpenAlexW3135409019MaRDI QIDQ2029543

Marc Sturrock, Ayoub Lasri

Publication date: 3 June 2021

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2021.110662

zbMATH Keywords

modellingdrug resistanceglioblastomamethylationMGMT

Mathematics Subject Classification ID

Medical applications (general) (92C50) Cell biology (92C37) Pathology, pathophysiology (92C32)

Uses Software

• Julia
• UMAP

Cites Work

• Unnamed Item
• The mean and noise of stochastic gene transcription with cell division
• Bounded noises in physics, biology, and engineering
• Stochastic and deterministic simulations of heterogeneous cell population dynamics
• Dynamics, stability and inheritance of somatic DNA methylation imprints
• Adaptive approximate Bayesian computation for complex models
• Julia: A Fresh Approach to Numerical Computing

This page was built for publication: The influence of methylation status on a stochastic model of MGMT dynamics in glioblastoma: phenotypic selection can occur with and without a downshift in promoter methylation status