Background Automated extraction of protein-protein interactions (PPI) is an important and
widely studied task in biomedical text mining. We propose a graph kernel based approach …

Protein–protein interaction (PPI) extraction is an important and widely researched task in the
biomedical natural language processing (BioNLP) field. Kernel-based machine learning …

Motivation: While text mining technologies for biomedical research have gained popularity
as a way to take advantage of the explosive growth of information in text form in biomedical …

The wealth of interaction information provided in biomedical articles motivated the
implementation of text mining approaches to automatically extract biomedical relations. This …

We introduce a relation extraction method to identify the sentences in biomedical text that
indicate an interaction among the protein names mentioned. Our approach is based on the …

Abstract Knowledge about protein–protein interactions is essential for understanding the
biological processes such as metabolic pathways, DNA replication, and transcription etc …

Natural language processing (NLP) has become an essential technique in various fields,
offering a wide range of possibilities for analyzing data and developing diverse NLP tasks. In …

We explore a rule-based methodology for the BioNLP'09 Shared Task on Event Extraction,
using dependency parsing as the underlying principle for extracting and characterizing …

Motivation: Identification and characterization of protein–protein interactions (PPIs) is one of
the key aims in biological research. While previous research in text mining has made …

In this paper, we propose a graph kernel based approach for the automated extraction of
protein-protein interactions (PPI) from scientific literature. In contrast to earlier approaches to …