Stochastic errors vs. modeling errors in distance based phylogenetic reconstructions

Authors:
Daniel Doerr;Ilan Gronau;Shlomo Moran;Irad Yavneh
Affiliations:
Center for Biotechnology, Bielefeld University, Bielefeld, Germany;Dept. of Biological Statistics and Computational Biology, Cornell University, Ithaca;Computer Science Dept., Technion-Israel Institute of Technology, Haifa, Israel;Computer Science Dept., Technion-Israel Institute of Technology, Haifa, Israel
Venue:
WABI'11 Proceedings of the 11th international conference on Algorithms in bioinformatics
Year:
2011

Citing 3
Cited 1

A few logs suffice to build (almost) all trees (l): part I

Random Structures & Algorithms
Pattern Recognition and Machine Learning (Information Science and Statistics)

Pattern Recognition and Machine Learning (Information Science and Statistics)
Stochastic errors vs. modeling errors in distance based phylogenetic reconstructions

WABI'11 Proceedings of the 11th international conference on Algorithms in bioinformatics

Stochastic errors vs. modeling errors in distance based phylogenetic reconstructions

WABI'11 Proceedings of the 11th international conference on Algorithms in bioinformatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Distance based phylogenetic reconstruction methods use the evolutionary distances between species in order to reconstruct the tree spanning them. This paper continues the line of research which attempts to adjust to each given set of input sequences a distance function which maximizes the expected accuracy of the reconstructed tree. We demonstrate both analytically and experimentally that by deliberately assuming an oversimplified evolutionary model, it is possible to increase the accuracy of reconstruction.