Chemical Entity Recognition and Resolution to ChEBI
Open Access
- 15 February 2012
- journal article
- Published by Hindawi Limited in ISRN Bioinformatics
- Vol. 2012, 1-9
- https://doi.org/10.5402/2012/619427
Abstract
Chemical entities are ubiquitous through the biomedical literature and the development of text-mining systems that can efficiently identify those entities are required. Due to the lack of available corpora and data resources, the community has focused its efforts in the development of gene and protein named entity recognition systems, but with the release of ChEBI and the availability of an annotated corpus, this task can be addressed. We developed a machine-learning-based method for chemical entity recognition and a lexical-similarity-based method for chemical entity resolution and compared them with Whatizit, a popular-dictionary-based method. Our methods outperformed the dictionary-based method in all tasks, yielding an improvement in F-measure of 20% for the entity recognition task, 2–5% for the entity-resolution task, and 15% for combined entity recognition and resolution tasks.Keywords
Funding Information
- European Commission (231807)
This publication has 21 references indexed in Scilit:
- Semantic Similarity for Automatic Classification of Chemical CompoundsPLoS Computational Biology, 2010
- Cascaded classifiers for confidence-based chemical named entity recognitionBMC Bioinformatics, 2008
- Linking genes to literature: text mining, information extraction, and retrieval applications for biologyGenome Biology, 2008
- Overview of BioCreative II gene mention recognitionGenome Biology, 2008
- Detection of IUPAC and IUPAC-like chemical namesBioinformatics, 2008
- Overview of BioCreative II gene normalizationGenome Biology, 2008
- ChEBI: a database and ontology for chemical entities of biological interestNucleic Acids Research, 2007
- Frontiers of biomedical text mining: current progressBriefings in Bioinformatics, 2007
- A scalable machine-learning approach to recognize chemical names within large text databasesBMC Bioinformatics, 2006
- Term identification in the biomedical literatureJournal of Biomedical Informatics, 2004