Identifying parsimonious pathways of accumulation and convergent evolution from binary data.

The article discusses the identification of parsimonious pathways of accumulation and convergent evolution from binary data in various processes, including genome evolution and cancer progression. The study focuses on minimizing a topological cost function to determine subgraphs that can generate specific observations before and after certain events. The research aims to measure the predictability and stereotypical nature of evolutionary processes, with applications in antimicrobial resistance, organelle genomes, and cancer progression. The preprint has not yet undergone peer review and provides a software implementation for further exploration. [Extracted from the article]