FlowerPower is a clustering algorithm designed for the identification of global homologs. It employs an iterative approach to clustering sequences. However, rather than using a single HMM or profile to expand the cluster, FlowerPower identifies subfamilies using the SCI-PHY algorithm and then selects and aligns new homologs using subfamily hidden Markov models. FlowerPower is shown to outperform BLAST, PSI-BLAST and the UCSC SAM-Target 2K methods at discrimination between proteins in the same domain architecture class and those having different overall domain structures.
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BMC Evol Biol. 2007 Feb 8;7 Suppl 1:S12.
FlowerPower: clustering proteins into domain architecture classes for phylogenomic inference of protein function.
Krishnamurthy N, Brown D, Sjölander K.