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A cubic algorithm for the generalized rank median of three genomes.

Leonid ChindelevitchSean LaJoao Meidanis
Published in: Algorithms for molecular biology : AMB (2019)
We test our method on both simulated and real data. We find that the majority of the realistic inputs result in genomic outputs, and for those that do not, our two heuristics perform well in terms of reconstructing a genomic matrix attaining a score close to the lower bound, while running in a reasonable amount of time. We conclude that the rank distance is not only theoretically intriguing, but also practically useful for median-finding, and potentially ancestral genome reconstruction.
Keyphrases
  • copy number
  • machine learning
  • electronic health record
  • deep learning
  • genome wide
  • gene expression