GDReCo: Fine-grained gene-disease relationship extraction corpus.

Journal: Computer methods and programs in biomedicine
PMID: 40245607

Abstract

BACKGROUND AND OBJECTIVE: Understanding gene-disease relationships is crucial for medical research, drug discovery, clinical diagnosis, and other fields. However, there is currently no high-quality, fine-grained corpus available for training Natural Language Processing (NLP) models, which have proven to be effective in knowledge extraction.

Authors

  • Hui Yu
    Engineering Technology Research Center of Shanxi Province for Opto-Electric Information and Instrument, Taiyuan 030051, China. 13934603474@nuc.edu.cn.
  • Jing Wu
    School of Pharmaceutical Science, Jiangnan University, Wuxi, 214122, Jiangsu, China.
  • Suyan Bian
    Department of Cardiology, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
  • Sheng Zhang
    Department of Critical Care Medicine, Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Taizhou, China.
  • Yibin Wu
    School of Software Engineering, Beijing Jiaotong University, Beijing, 100044, China.
  • Ziyan Zhou
    Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China.
  • Qian Jia
    Beijing Key Laboratory for Precision Medicine of Chronic Heart Failure, Chinese PLA General Hospital, Beijing, China.
  • Yuan Ni
    IBM Research, China, Beijing, China.
  • Zhengxing Huang
    College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
  • Huiyu Yan
    Department of Anesthesiology, Beijing Stomatological Hospital, Capital Medical University, Beijing, China.
  • Weidong Wang
    Zhejiang Huade New Materials Co., Ltd., Zhejiang Province, Hangzhou, China.
  • Kunlun He
    Beijing Key Laboratory of Precision Medicine for Chronic Heart Failure, Chinese PLA General Hospital, Beijing, China.
  • Jinlong Shi
    Department of Medical Innovation Research, Medical Big Data Center, Chinese PLA General Hospital, Beijing, China.

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