Abstract

We evaluate our approach on two protein classi?cation tasks involving the prediction of SCOP structural classes and catalytic activity according to the Gene Ontology. We provide evidence that the method is competitive when compared to string kernels, and useful for a range of protein classi?cation tasks. Furthermore, the applicability of our approach extends beyond computational biology to any classi?cation of time series data.