Pattern Detection on Glioblastoma’s Waddington Landscape via Generative Adversarial Networks

@article{Uthamacumaran2021PatternDO,
  title={Pattern Detection on Glioblastoma’s Waddington Landscape via Generative Adversarial Networks},
  author={Abicumaran Uthamacumaran},
  journal={Cybernetics and Systems},
  year={2021}
}
Glioblastoma (GBM) is a highly morbid and lethal disease with poor prognosis. Their emergent properties such as cellular heterogeneity, therapy resistance, and self-renewal are largely attributed to the interactions between a subset of their population known as glioblastoma-derived stem cells (GSCs) and their microenvironment. Identifying causal patterns in the developmental trajectories between GSCs and the mature, well-differentiated GBM phenotypes remains a challenging problem in oncology… Expand

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