Efficiently Computing Arbitrarily-Sized Robinson-Foulds Distance Matrices

@inproceedings{Sul2008EfficientlyCA,
  title={Efficiently Computing Arbitrarily-Sized Robinson-Foulds Distance Matrices},
  author={Seung-Jin Sul and Grant R. Brammer and Tiffani L. Williams},
  booktitle={WABI},
  year={2008}
}
In this paper, we introduce the HashRF(p,q) algorithm for computing RF matrices of large binary, evolutionary tree collections. The novelty of our algorithm is that it can be used to compute arbitrarily-sized (p×q) RF matrices without running into physical memory limitations. In this paper, we explore the performance of our HashRF(p,q) approach on 20,000 and 33,306 biological trees of 150 taxa and 567 taxa trees, respectively, collected from a Bayesian analysis. When computing the all-to-all RF… 
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