https://hal-lirmm.ccsd.cnrs.fr/lirmm-01236880Pardi, FabioFabioPardiMAB - Méthodes et Algorithmes pour la Bioinformatique - LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier - UM - Université de Montpellier - CNRS - Centre National de la Recherche ScientifiqueThe combinatorics of distance-based tree inferenceHAL CCSD2011[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]Pardi, Fabio2015-12-02 11:49:182022-08-05 15:02:172015-12-18 18:12:01enConference papers1Several 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 combinatorial 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 efficient search algorithms for distance-based tree reconstruction.