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Computational and Mathematical Methods in Medicine - Volume 2015 2015, Article ID 571381, 19 pages -

Review Article

MindLab Research Laboratory, Universidad Nacional de Colombia, Bogotá, Colombia

DETI-IEETA, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal

Received 13 May 2015; Revised 10 August 2015; Accepted 18 August 2015

Academic Editor: Chuan Lu

Copyright © 2015 Jorge A. Vanegas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a review of state-of-the-art approaches to automatic extraction of biomolecular events from scientific texts. Events involving biomolecules such as genes, transcription factors, or enzymes, for example, have a central role in biological processes and functions and provide valuable information for describing physiological and pathogenesis mechanisms. Event extraction from biomedical literature has a broad range of applications, including support for information retrieval, knowledge summarization, and information extraction and discovery. However, automatic event extraction is a challenging task due to the ambiguity and diversity of natural language and higher-level linguistic phenomena, such as speculations and negations, which occur in biological texts and can lead to misunderstanding or incorrect interpretation. Many strategies have been proposed in the last decade, originating from different research areas such as natural language processing, machine learning, and statistics. This review summarizes the most representative approaches in biomolecular event extraction and presents an analysis of the current state of the art and of commonly used methods, features, and tools. Finally, current research trends and future perspectives are also discussed.

Autor: Jorge A. Vanegas, Sérgio Matos, Fabio González, and José L. Oliveira



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