A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Distance Measures for Tumor Evolutionary Trees
2019
Bioinformatics
Motivation There has been recent increased interest in using algorithmic methods to infer the evolutionary tree underlying the developmental history of a tumor. Quantitative measures that compare such trees are vital to a number of different applications including benchmarking tree inference methods and evaluating common inheritance patterns across patients. However, few appropriate distance measures exist, and those that do have low resolution for differentiating trees or do not fully account
doi:10.1093/bioinformatics/btz869
pmid:31750900
pmcid:PMC7141873
fatcat:l2kiwyirirdjzjungkhhodya3a