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Integration of the PubAnnotation ecosystem in the development of a web-based search tool for alternative methods

  • Neves, Mariana (German Federal Institute for Risk Assessment (BfR), German Centre for the Protection of Laboratory Animals (Bf3R))
  • 투고 : 2020.03.13
  • 심사 : 2020.05.28
  • 발행 : 2020.05.28

초록

Finding publications that propose alternative methods to animal experiments is an important but time-consuming task since researchers need to perform various queries to literature databases and screen many articles to assess two important aspects: the relevance of the article to the research question, and whether the article's proposed approach qualifies to being an alternative method. We are currently developing a Web application to support finding alternative methods to animal experiments. The current (under development) version of the application utilizes external tools and resources for document processing, and relies on the PubAnnotation ecosystem for annotation querying, annotation storage, dictionary-based tagging of cell lines, and annotation visualization. Currently, our two PubAnnotation repositories for discourse elements contain annotations for more than 110k PubMed documents. Further, we created an annotator for cell lines that contain more than 196k terms from Cellosaurus. Finally, we are experimenting with TextAE for annotation visualization and for user feedback.

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참고문헌

  1. Kim JD, Wang Y, Fujiwara T, Okuda S, Callahan TJ, Cohen KB. Open Agile text mining for bioinformatics: the PubAnnotation ecosystem. Bioinformatics 2019;35:4372-4380. https://doi.org/10.1093/bioinformatics/btz227
  2. Lin J, Wilbur WJ. PubMed related articles: a probabilistic topic-based model for content similarity. BMC Bioinformatics 2007;8:423. https://doi.org/10.1186/1471-2105-8-423
  3. Bairoch A. The Cellosaurus, a cell-line knowledge resource. J Biomol Tech 2018;29:25-38. https://doi.org/10.7171/jbt.18-2902-002
  4. Mrabet Y, Kilicoglu H, Demner-Fushman D. TextFlow: a text similarity measure based on continuous sequences. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Vol. 1, Long Papers) (Barzilay R, Kan MY, eds.), 2017 Jul 30-Aug 4, Vancouver, Canada. Stroudsburg: Association for Computational Linguistics, 2017. pp. 763-772.
  5. Neves M, Butzke D, Grune B. Evaluation of scientific elements for text similarity in biomedical publications. In: Proceedings of the 6th Workshop on Argument Mining (Stein B, Wachsmuth H, eds.), 2019 Aug 1, Florence, Italy. Stroudsburg: Association for Computational Linguistics, 2019. pp. 124-135.
  6. Lauscher A, Glavas G, Eckert K. ArguminSci: a tool for analyzing argumentation and rhetorical aspects in scientific writing. In: Proceedings of the 5th Workshop on Argument Mining, 2018 Nov, Brussels, Belgium. Stroudsburg: Association for Computational Linguistics, 2018. pp. 22-28.
  7. Wei CH, Allot A, Leaman R, Lu Z. PubTator central: automated concept annotation for biomedical full text articles. Nucleic Acids Res 2019;47:W587-W593. https://doi.org/10.1093/nar/gkz389