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Protein Complex Mention Recognition with Web-Based Knowledge Learning

  • Ruoyao Ding
  • Xiaoyi Pan
  • Yingying Qu
  • Cathy H. Wu
  • K. Vijay-Shanker
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11284)

Abstract

Protein complex plays an essential role in cellular functions and is an important named entity in the biomedical field. Since protein complex –relevant experimental results are usually published in scientific articles, recognizing protein complex mentions from literature is a crucial step of discovering protein complex-related information from existing scientific research studies. In this paper, we propose a method for protein complex mention recognition, which applies knowledge automatically learned from PubMed. Evaluation shows our method achieves a F1-score of 81%, demonstrating its effectiveness in the protein complex recognition task.

Keywords

Named entity recognition Protein complex Conditional Random Field 

Notes

Acknowledgements

This paper is supported by grants from National Key R&D Program of China (2016YFF0204205, 2018YFF0213901) and China National Institute of Standardization (522016Y-4681, 522018Y-5948, 522018Y-5941).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Ruoyao Ding
    • 1
  • Xiaoyi Pan
    • 1
  • Yingying Qu
    • 2
  • Cathy H. Wu
    • 3
  • K. Vijay-Shanker
    • 3
  1. 1.School of Information Science and TechnologyGuangdong University of Foreign StudiesGuangzhouChina
  2. 2.School of BusinessGuangdong University of Foreign StudiesGuangzhouChina
  3. 3.Department of Computer and Information ScienceUniversity of DelawareNewarkUSA

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