Tommi Jaakkola Mark Diekhans, David Haussler
Abstract
A new method, called the Fisher
kernel method, for detecting remote protein homologies is introduced
and shown to perform well in classifying protein domains by SCOP
superfamily. The method is a variant of support vector machines
using a new kernel function. The kernel function is derived from
a hidden Markov model. The general approach of combining generative
models like HMMs with discriminative methods such as support vector
machines may have applications in other areas of biosequence analysis
as well.