Detection of Interaction Articles and Experimental Methods in Biomedical Literature

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2011 Dec 14

PMID 22151872

Citations 8

Authors

Gerold Schneider

Simon Clematide

Fabio Rinaldi

Affiliations

Soon will be listed here.

Abstract

Background: This article describes the approaches taken by the OntoGene group at the University of Zurich in dealing with two tasks of the BioCreative III competition: classification of articles which contain curatable protein-protein interactions (PPI-ACT) and extraction of experimental methods (PPI-IMT).

Results: Two main achievements are described in this paper: (a) a system for document classification which crucially relies on the results of an advanced pipeline of natural language processing tools; (b) a system which is capable of detecting all experimental methods mentioned in scientific literature, and listing them with a competitive ranking (AUC iP/R > 0.5).

Conclusions: The results of the BioCreative III shared evaluation clearly demonstrate that significant progress has been achieved in the domain of biomedical text mining in the past few years. Our own contribution, together with the results of other participants, provides evidence that natural language processing techniques have become by now an integral part of advanced text mining approaches.

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Automatic query generation using word embeddings for retrieving passages describing experimental methods.

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Detection and categorization of bacteria habitats using shallow linguistic analysis.

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