They often exhibit state-of-the-art performance on many practical tasks of sequence analysis such as biological sequence classification, remote homology detection, or protein superfamily and fold prediction.
Typical string kernel methods rely on analysis of discrete one-dimensional (1 D) string data (e.g., DNA or amino acid sequences).