Supertree methods combine trees on subsets of a taxon set together to
produce a tree on the entire set of taxa. SuperFine is a meta-method
that utilizes a novel two-step procedure in order to improve the
accuracy and scalability of supertree methods. Studies using both
simulated and empirical data have shown that SuperFine-boosted
supertree methods produce more accurate trees than standard supertree
methods, and run more quickly particularly on very large datasets. We
present an overview of the SuperFine approach, compare the performance
of boosted and unboosted methods on simulated and empirical data, and
describe other novel phylogenetic applications that incorporate
SuperFine-boosted supertree methods.