arXiv · 2407.19330
Unveiling Cancer Stem Cell Marker Networks: A Hypergraph Approach
Abstract
We propose a novel computational framework leveraging hypergraph theory to analyse cancer stem cell markers (CSCMs) across multiple organs. Hypergraphs provide a robust representation of CSCM co-expression patterns, capturing their complex multi-organ relationships more comprehensively than traditional graph-based methods. By integrating mutual information analysis and Markov models, we identify key markers driving tumour heterogeneity and metastasis, offering detailed insights into their interdependencies. This approach establishes hypergraphs as a computationally powerful tool to model cancer progression and metastatic dynamics, contributing to the understanding of complex biological systems and supporting the development of targeted therapeutic strategies.
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David H. Margarit, Gustavo Paccosi, Marcela V. Reale, Lilia M. Romanelli. 2024-07-27. Unveiling Cancer Stem Cell Marker Networks: A Hypergraph Approach. https://arxiv.org/abs/2407.19330
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