Uncovering the role of mutations in Epithelial-to-Mesenchymal transition through computational analysis of the underlying gene regulatory network

10 pages•Published: May 1, 2023

Abstract

We illustrate here a systems-based computational analysis technique intended for uncov- ering dynamic properties of gene regulatory networks described in discrete Boolean terms. This through the use of the algebraic Semi-Tensor Product (STP), and with the purpose of exploring the regulatory consequences of genetic mutations in the modification of cell phenotypes. The proposed technique derives from the state-based reachability analysis of dynamic systems via the design of open-loop perturbative control schemes. We choose as a case-of-study the discrete Boolean network that describes in qualitative formal terms the transcriptional gene regulatory network that underlies the Epithelial-to-Mesenchymal transition in the context of epithelial cancer. We are particularly interested in qualitatively understanding the systems level consequences of mutations in specific genes that regulate the phenotypic transition. More specifically, we are interested in bringing to light potential preventive therapeutic interventions that promote the Mesenchymal-to-Epithelial transition.

Keyphrases: Attractors landscape, Discrete Boolean networks, Epithelial cancer, epithelial-to-mesenchymal transition, gene mutations, gene regulatory networks, medical systems biology, reachability analysis, semi-tensor product

In: Hisham Al-Mubaid, Tamer Aldwairi and Oliver Eulenstein (editors). Proceedings of International Conference on Bioinformatics and Computational Biology (BICOB-2023), vol 92, pages 92--101

Links:	https://easychair.org/publications/paper/XKhd
	https://doi.org/10.29007/pxl5