CHEMDNER task: Chemical compound and drug name recognition task
(1) TASK GOAL AND MOTIVATION
The goal of this task is to promote the implementation of systems that are able to detect mentions in text of chemical compounds and drugs. The recognition of chemical entities is also crucial for other subsequent text processing strategies, such as detection of drug-protein interactions, adverse effects of chemical compounds or the extraction of pathway and metabolic reaction relations. A range of methods have been explored to the recognition of chemical compound mentions, including machine learning techniques, rule-bases approaches and different dictionary-lookup strategies.
We foresee a considerable interest in the result of this task by the NLP/text mining community on one side, as well as by the bioinformatics, drug discovery/biomedicine and chemoinformatics communities on the other side. As has been the case in previous BioCreative efforts (resulting in high impact papers in the field), we expect that successful participants will have the opportunity to publish their system descriptions in a journal article.
(2) CHEMDNER TRACK DESCRIPTION
The CHEMDNER is one of the tracks posed at the BioCreative IV community challenge www.biocreative.org
We invite participants to submit results for the CHEMDNER task providing predictions for one or both of the following subtasks:
a) Given a set of documents, return for each of them a ranked list of chemical entities described within each of these documents [Chemical document indexing sub-task]
b) Provide for a given document the start and end indices corresponding to all the chemical entities mentioned in this document [Chemical entity mention recognition sub-task].
For these two tasks the organizers will release training and test data collections. The task organizers will provide details on the used annotation guidelines; define a list of criteria for relevant chemical compound entity types as well as selection of documents for annotation.
(3) REGISTRATION
Teams can participate in the CHEMDNER task by registering for track 2 of BioCreative IV. You can register additionally for other tracks too. To register your team, go to the following page that provides more detailed instructions:
www.biocreative.org/news/biocreative-iv/team/
(4) WORKSHOP
CHEMDNER is part of the BioCreative evaluation effort. The BioCreative Organizing Committee will host the BioCreative IV Challenge evaluation workshop (www.biocreative.org/events/biocreative-iv/CFP/) at NCBI, National Institutes of
Health, Bethesda, Maryland, on October 7-9, 2013
(5) CHEMDNER TASK ORGANIZERS
- Martin Krallinger, Spanish National Cancer Research Center (CNIO)
- Obdulia Rabal, University of Navarra, Spain
- Julen Oyarzabal, University of Navarra, Spain
- Alfonso Valencia, Spanish National Cancer Research Center (CNIO)
- Vazquez, M., Krallinger, M., Leitner, F., & Valencia, A. (2011). Text Mining for Drugs and Chemical Compounds: Methods, Tools and Applications. Molecular Informatics, 30(6:7), 506-519.
- Krallinger M, et al. The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text. BMC Bioinformatics. 2011;12 Suppl 8:S3
- Corbett, P., Batchelor, C., & Teufel, S. (2007). Annotation of chemical named entities. BioNLP 2007: Biological, translational, and clinical language processing, 57-64.
- Klinger, R., Kolarik, C., Fluck, J., Hofmann-Apitius, M., & Friedrich, C. M. (2008). Detection of IUPAC and IUPAC-like chemical names. Bioinformatics, 24(13), i268-i276.
- Hettne, K. M., Stierum, R. H., Schuemie, M. J., Hendriksen, P. J., Schijvenaars, B. J., Mulligen, E. M. V., ... & Kors, J. A. (2009). A dictionary to identify small molecules and drugs in free text. Bioinformatics, 25(22), 2983-2991.
- Yeh, A., Morgan, A., Colosimo, M., & Hirschman, L. (2005). BioCreAtIvE task 1A: gene mention finding evaluation. BMC bioinformatics, 6(Suppl 1), S2.
- Smith, L., Tanabe, L. K., Ando, R. J., Kuo, C. J., Chung, I. F., Hsu, C. N., ... & Wilbur, W. J. (2008). Overview of BioCreative II gene mention recognition. Genome Biology, 9(Suppl 2), S2.
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