Walk-weighted subsequence kernels for protein-protein interaction extraction

Background: The construction of interaction networks between proteins is central to understanding the underlying biological processes. However, since many useful relations are excluded in databases and remain hidden in raw text, a study on automatic interaction extraction from text is important in bioinformatics field. Results: Here, we suggest two kinds of kernel methods for genic interaction extraction, considering the structural aspects of sentences. First, we improve our prior dependency kernel by modifying the kernel function so that it can involve various substructures in terms of (1) e-walks, (2) partial match, (3) non-contiguous paths, and (4) different significance of substructures. Second, we propose the walk-weighted subsequence kernel to parameterize non-contiguous syntactic structures as well as semantic roles and lexical features, which makes learning structural aspects from a small amount of training data effective. Furthermore, we distinguish the significances of param...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Seonho Kim, Juntae Yoon, Jihoon Yang, Seog Park
• Keywords: BMCBI 2010, Genic Interaction, Interaction Extraction, Walk-weighted Subsequence Kernel