- (Fundel et al., 2007) ⇒ Katrin Fundel, Robert Kuffner, Ralf Zimmer. (2007). “RelEx - Relation Extraction Using Dependency Parse Trees.” In: Bioinformatics, 23(3).
- Gene and protein names are identified by ProMiner System. (Hanisch et al., 2005)
- Ranked #1 for two of three NER tests in BioCreative
- It is based on matching to a synonym dictionary (Fundel and Zimmer, 2006)
Motivation: The discovery of regulatory pathways, signal cascades, metabolic processes or disease models requires knowledge on individual relations like e.g. physical or regulatory interactions between genes and proteins. Most interactions mentioned in the free text of biomedical publications are not yet contained in structured databases.
Results: We developed RelEx, an approach for relation extraction from free text. It is based on natural language preprocessing producing dependency parse trees and applying a small number of simple rules to these trees. We applied RelEx on a comprehensive set of one million MEDLINE abstracts dealing with gene and protein relations and extracted ~150 000 relations with an estimated perfomance of both 80% precision and 80% recall.
Availability: The used natural language preprocessing tools are free for use for academic research. Test sets and relation term lists are available from our website (http://www.bio.ifi.lmu.de/publications/RelEx/).
- Blaschke, C. et al. (1999) Automatic extraction of biological information from scientific text: protein-protein interactions. Proceedings of International Conference Intell. Syst. Mol. Biol., 60–67.
- Blaschke, C. and Valencia, A. (2001) The potential use of suiseki as a protein interaction discovery tool. Genome Inform. Ser. Workshop Genome Inform., 12, 123–134.
- (DingBNW, 2002) ⇒ J. Ding, D. Berleant, D. Nettleton, and E. Wurtelec. (2002). “Mining Medline: Abstracts, Sentences, or Phrases?” Pacific Symposium on Biocomputing 7:326-337.
- (JelierJDEMMK, 2005) ⇒ R. Jelier, G. Jenster, L. C. J. Dorssers, C. C. van der Eijk, E. M. van Mulligen, B. Mons, and J. A. Kors. (2005). “Co-occurrence based meta-analysis of scientific texts: retrieving biological relationships between genes. Bioinformatics, 21, 2049–2058.
- Jenssen, T.K. et al. (2001) A literature network of human genes for high-throughput analysis of gene expression. Nat. Genet., 28, 21–28.
- Fundel, K. and Zimmer, R. (2006) Gene and protein nomenclature in public databases. BMC Bioinformatics, 7, 372.
- (Hanisch et al., 2005) ⇒ Daniel Hanisch, Katrin Fundel, Heinz-Theodor Mevissen, Ralf Zimmer and Juliane Fluck. (2005). “Prominer: Rule-based protein and gene entity recognition. BMC Bioinformatics, 6 (Suppl 1), S14.
- Klein, D. and Manning, C.D. (2002). Fast exact inference with a factored model for natural language parsing. Adv. Neural Inform. Proceedings of Syst., 15, 3–10.
- Klein, D. and Manning, C.D. (2003). Accurate unlexicalized parsing. In: Proceedings of the 41st Meeting of the Association for Computational Linguistics.
- Leroy, G. and Chen, H. (2002). Filling preposition-based templates to capture information from medical abstracts. Pac. Symp. Biocomput., 7, 350–361.
- Mel’cuk, I. (1988) Dependency Syntax: Theory and Practice. State University Press of New York, NY.
- Ono, T. et al. (2001) Automated extraction of information on protein–protein interactions from the biological literature. Bioinformatics, 17, 155–161.,
|2007 RelExRelExtrUsingDepParseTrees||Katrin Fundel|
|RelEx - Relation Extraction Using Dependency Parse Trees||The Bioinformatics Journal||http://www.biomedcentral.com/content/pdf/1471-2105-6-S1-S14.pdf||2007|