PMCE: efficient inference of expressive models of cancer evolution with high prognostic power

@article{Angaroni2021PMCEEI,
  title={PMCE: efficient inference of expressive models of cancer evolution with high prognostic power},
  author={Fabrizio Angaroni and Kevin Chen and Chiara Damiani and Giulio Caravagna and Alex Graudenzi and Daniele Ramazzotti},
  journal={bioRxiv},
  year={2021}
}
Motivation Driver (epi)genomic alterations underlie the positive selection of cancer subpopulations, which promotes drug resistance and relapse. Even though substantial heterogeneity is witnessed in most cancer types, mutation accumulation patterns can be regularly found and can be exploited to reconstruct predictive models of cancer evolution. Yet, available methods cannot infer logical formulas connecting events to represent alternative evolutionary routes or convergent evolution. Results We… 

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