Maximum-Likelihood Model Averaging To Profile Clustering of Site Types across Discrete Linear Sequences

JeffreyTownsend — Mon, 10 Aug 2009 08:22:23 -0700

A major analytical challenge in computational biology is the detection and description of clusters of specified site types, such as polymorphic or substituted sites within DNA or protein sequences. Progress has been stymied by a lack of suitable methods to detect clusters and to estimate the extent of clustering in discrete linear sequences, particularly when there is no a priori specification of cluster size or cluster count. Here we derive and demonstrate a maximum likelihood method of hierarchical clustering.

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