CALL FOR PARTICIPATION: CHEMDNER task: Chemical compound and drug name recognition task
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The CHEMDNER task (part of The BioCreative IV competition) is a community challenge on named entity recognition of chemical compounds.

CRFs were used successfully as a method for named entity recognition (NER) by teams that participated in previous

BioCreative challenges. We expect that the CRF package will be a useful resource also for the chemical compound

name recognition task. We thus encourage CRF Packaged users to participate at the chemical compound named

entity recognition task of BioCreative IV.

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 different methods have been explored for the recognition of chemical compound mentions including machine learning based approaches, rule-based systems and different types of dictionary-lookup strategies. The Weka framework has been successfully explored by several participating teams for previous biomedical text mining task posed in the context of the BioCreative challenge.

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.

The CHEMDNER is one of the tracks posed at the BioCreative IV community challenge (

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.

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:

Mailing list and contact information:
You can post questions related to the CHEMDNER task to the BioCreative mailing list. To register for the BioCreative mailing list, please visit the following page:

CHEMDNER is part of the BioCreative evaluation effort. The BioCreative Organizing Committee will host the BioCreative IV Challenge evaluation workshop ( at NCBI, National Institutes of Health, Bethesda, Maryland, on October 7-9, 2013


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)


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- Klinger, R., Kolářik, C., Fluck, J., Hofmann-Apitius, M., & Friedrich, C. M. (2008). Detection of IUPAC and IUPAC-like chemical names. Bioinformatics, 24(13), i268-i276.
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