The Taub Faculty of Computer Science Events and Talks

Distance based reconstruction methods of phylogenetic trees consist of two independent parts: first, inter-species distances are estimated assuming some stochastic model of sequence evolution; then the inferred distances are used to construct the tree. These methods rely heavily on comparisons of the inferred distances and of linear combinations thereof. In this work we show how to accurately and efficiently compare two evolutionary distances, and set the ground for more complicated comparisons (e.g., comparisons of sums of distances, used in the 4 points method for quartets reconstruction). The methods we developed continue a line of research that characterized the family of valid distance functions for the assumed evolution model (substitution rate (SR) functions) and showed that deliberate selection of a distance function significantly improves the accuracy of distance estimates. We present the DiscScore method to adaptively select an SR function that compares two given paths with accuracy of maximum-likelihood based methods, while being more computationally efficient, and avoiding the need of certain assumptions on the model (homogeneity).