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BioCreative V.5

BioCreative V5BioCreative (Critical Assessment of Information Extraction in Biology) is an international, community-wide effort for evaluating text mining and information extraction systems applied to the biological and biochemical domains (http://www.biocreative.org/). The Challenge Evaluations and the accompanying BioCreative Workshops bring the text mining and biomedical communities together and drive the development of text mining systems to meet critical research needs, resulting in novel applications that can be integrated into the knowledge discovery process.

Edited by Martin Krallinger, Obdulia Rabal, Anália Lourenço, Alfonso Valencia

  1. We present a text-mining tool for recognizing biomedical entities in scientific literature. OGER++ is a hybrid system for named entity recognition and concept recognition (linking), which combines a dictionary...

    Authors: Lenz Furrer, Anna Jancso, Nicola Colic and Fabio Rinaldi

    Citation: Journal of Cheminformatics 2019 11:7

    Content type: Research article

    Published on:

  2. The need to efficiently find and extract information from the continuously growing biomedical literature has led to the development of various annotation tools aimed at identifying mentions of entities and rel...

    Authors: Sérgio Matos

    Citation: Journal of Cheminformatics 2018 10:68

    Content type: Research article

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  3. In biomedical research, patents contain the significant amount of information, and biomedical text mining has received much attention in patents recently. To accelerate the development of biomedical text minin...

    Authors: Ling Luo, Zhihao Yang, Pei Yang, Yin Zhang, Lei Wang, Jian Wang and Hongfei Lin

    Citation: Journal of Cheminformatics 2018 10:65

    Content type: Research article

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  4. Recent years showed a strong increase in biomedical sciences and an inherent increase in publication volume. Extraction of specific information from these sources requires highly sophisticated text mining and ...

    Authors: Johannes Kirschnick, Philippe Thomas, Roland Roller and Leonhard Hennig

    Citation: Journal of Cheminformatics 2018 10:63

    Content type: Research article

    Published on: