Background
Extraction of protein-protein interactions (PPIs) reported in scientific publications is a core topic of biomedical text mining. The ultimate goal is to devise a PPI extraction method that performs well on large amount of unseen text independently from the training corpus. One popular, machine-learning based approach to PPI extraction builds on the convolution kernels, i.e., similarity functions defined on the parse-based representation of sentences and interactions. Kernel functions differ in (1) the underlying sentence representation (bag-of-words, syntax tree parse, dependency graphs), (2) the substructures retrieved from the sentence representation to define interactions, and (3) calculation of the similarity function.