Woven string kernels for DNA sequence classification

Abstract

Woven string kernels are a form of evolvable directed acyclic graph specialized to perform DNA classification. They are introduced in this study and tested on simple and complex synthetic data as well as biological data. The WSKs perform marginally on the simplest synthetic data - based on GC content - for which they are not entirely appropriate. They exhibit perfect classification on the more complex synthetic data and on the biological data. Woven string kernels have a number of parameters including their height, the number of initial strings from which they are built, and the amount of “weaving” used to generate the final structure. A parameter study shows that these parameters must be set based on the type of data under analysis. The paper concludes with comments on possible improvements of the woven string kernel technique.