Kernel design for RNA classification using Support Vector Machines

@article{Wang2006KernelDF,
  title={Kernel design for RNA classification using Support Vector Machines},
  author={Jason Tsong-Li Wang and Xiaoming Wu},
  journal={International journal of data mining and bioinformatics},
  year={2006},
  volume={1 1},
  pages={57-76}
}
Support Vector Machines (SVMs) are a state-of-the-art machine learning tool widely used in speech recognition, image processing and biological sequence analysis. An essential step in SVMs is to devise a kernel function to compute the similarity between two data points. In this paper we review recent advances of using SVMs for RNA classification. In particular we present a new kernel that takes advantage of both global and local structural information in RNAs and uses the information together to… CONTINUE READING