State-of-the-art methods for protein-protein interaction (PPI) extraction are primarily feature-
based or kernel-based by leveraging lexical and syntactic information. But how to …

Background The wide variety of morphological variants of domain-specific technical terms
contributes to the complexity of performing natural language processing of the scientific …

Research on extracting biomedical relations has received growing attention recently, with
numerous biological and clinical applications including those in pharmacogenomics, clinical …

Drug development is an expensive and time-consuming process; these could be reduced if
the existing resources could be used to identify candidates for drug repurposing. This study …

We present an evaluation task designed to provide a frame-work for comparing different
approaches to extracting drug-drug interac-tions from biomedical texts. We define the task …

Pharmacovigilance (PV) is defined by the World Health Organization as the science and
activities related to the detection, assessment, understanding and prevention of adverse …

Medical relation extraction discovers relations between entity mentions in text, such as
research articles. For this task, dependency syntax has been recognized as a crucial source …

Objective To develop an open-source temporal relation discovery system for the clinical
domain. The system is capable of automatically inferring temporal relations between events …

Background Relation extraction from biomedical publications is an important task in the area
of semantic mining of text. Kernel methods for supervised relation extraction are often …

There is a surge of research interest in protein–protein interaction (PPI) extraction from
biomedical literature. While most of the state-of-the-art PPI extraction systems focus on …