PhyloHMM 

Phylogenetic hidden Markov models, or phylo-HMMs, are probabilistic models that consider not only the way substitutions occur through evolutionary history at each site of a genome, but also the way this process changes from one site to the next. By treating molecular evolution as a combination of two Markov processes—one that operates in the dimension of space (along a genome) and one that operates in the dimension of time (along the branches of a phylogenetic tree)—these models allow aspects of both sequence structure and sequence evolution to be captured. Moreover, they permit key computations to be performed exactly and efficiently. Phylo-HMMs allow evolutionary information to be brought to bear on a wide variety of problems of sequence “segmentation,” such as gene prediction and the identification of conserved elements. A phylo-HMM can be thought of as a machine that probabilistically generates a multiple alignment, column by column, such that each column is defined by a phylogenetic model. (http://compgen.bscb.cornell.edu/~acs/phylohmm.pdf )