A comprehensive benchmark of kernel methods to extract protein-protein interactions from literature.

ABSTRACT: The most important way of conveying new findings in biomedical research is scientific publication. Extraction of protein-protein interactions (PPIs) reported in scientific publications is one of the core topics of text mining in the life sciences. Recently, a new class of such methods has been proposed - convolution kernels that identify PPIs using deep parses of sentences. However, comparing published results of different PPI extraction methods is impossible due to the use of different evaluation corpora, different evaluation metrics, different tuning procedures, etc. In this paper, we study whether the reported performance metrics are robust across different corpora and learning settings and whether the use of deep parsing actually leads to an increase in extraction quality. Our ultimate

SUBMITTER: Tikk D 

PROVIDER: S-EPMC2895635 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature