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The combinatorics of distance-based tree inference

Pardi, F (CNRS)
Friday 24 June 2011, 10:40-11:00

Seminar Room 1, Newton Institute


Several popular methods for phylogenetic inference (or hierarchical clustering) are based on a matrix of pairwise distances between taxa (or any kind of objects): the objective is to construct a tree with branch lengths so that the distances between the leaves in that tree are as close as possible to the input distances. If we hold the structure (topology) of the tree fixed, in some relevant cases the optimal values for the branch lengths can be expressed using simple combinatiorial formulae. Here we define a general form for these formulae and show that they all have two desirable properties: first, the common tree reconstruction approaches (least squares, minimum evolution), when used in combination with these formulae, are guaranteed to infer the correct tree when given enough data (consistency); second, the branch lengths of all the simple (NNI) rearrangements of a tree can be calculated, optimally, in quadratric time in the size of the tree. The study presented here may form the basis for novel effcient search algorithms for distance-based tree reconstruction.


[pdf ]


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