Maximum Similarity: A New Formulation of Phylogenetic Reconstruction
We present a new formulation of phylogenetic reconstruction named maximum similarity. We describe basic algorithms based on the maximum similarity objective for computing distances between subtrees and for combining two subtrees. We present distance methods for constructing an initial tree and updating the initial tree by incorporating those basic algorithms into the Neighbor Joining (NJ) method and the Nearest-Neighbor Interchange (NNI) framework of the FastME program. The new distance methods have been implemented as a computer program named MS. The time requirement of the MS program is about five times the cost of computing observed sequence distances. The MS program was compared by simulation with four existing programs: NJ, FastME, STC, and Weighbor. Experimental results show that incorporating the maximum similarity objective into existing methods leads to improvements both in topology and in branch length.
distance methods maximum similarity score phylogenetic inference