Friday, 26 Feb 2021

Computational model of cell phenotype decision making

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Epithelial to Mesenchymal transition (EMT) is an exceedingly complex biological process that plays a key role in cancer progression and metastases formation. To unravel this complexity and isolate specific genetic markers important for this transition, we have developed a computational model recapitulating both single cell and population behaviours. The former was represented with a boolean network describing the major pathways involved in EMT, while the latter consisted in a Markov chain modeling the temporal evolution of the phenotypes (i.e. different gene expression patterns) throughout the transformation. This model was shown to have a good agreement with experimental results and to be able to identify a signature of genes with a key role EMT execution and progression.

computational model mcbeng

The source code used for this work can be downloaded here while the paper’s full text is freely available at

This work is part of the Research Topic: “Single-Cell Data Analysis: Resources, Challenges and Perspectives” of Frontiers in Genetics. Read the other works in this collection at

Published in Systems Biology
Marilisa Cortesi

Biomedical engineer graduated magna cum laude at the University of Bologna, Italy, in 2013. In 2017 she was awarded a PhD in Bioengineering from the same institution, with a thesis on computational modelling of complex biological processes and their application to the identification of potential therapeutic targets. More