Modeling adaptive kernels from probabilistic phylogenetic trees.

Objective: Modeling phylogenetic interactions is an open issue in many computational biology problems. In the context of gene function prediction we introduce a class of kernels for structured data leveraging on a hierarchical probabilistic modeling of phylogeny among species.

Methods And Materials: We derive three kernels belonging to this setting: a sufficient statistics kernel, a Fisher kernel, and a probability product kernel.