Intelligent larval zebrafish phenotype recognition via attention mechanism for high-throughput screening.

Journal: Computers in biology and medicine
PMID:

Abstract

BACKGROUND: Larval zebrafish phenotypes serve as critical research indicators in fields such as ecotoxicology and safety assessment since phenotypic defects are closely related to alterations of underlying pathway. However, identifying these defects is time-consuming and requires specialized knowledge.

Authors

  • Baihua Wang
    College of Biological Science and Engineering, Fuzhou University, Fuzhou, Fujian, China.
  • Qi Sun
    Department of Orthopedics, Shanghai Tenth People's Hospital, Tongji University, School of Medicine, Shanghai, 200072, P.R.China.
  • Yujia Liu
    The First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
  • Jiheng Zhang
    College of Biological Science and Engineering, Fuzhou University, Fuzhou, 350000, Fujian Province, China.
  • Gaozheng Li
    College of Computer and Data Science/College of Software, Fuzhou University, Fujian, China.
  • Sifang Wu
    College of Biological Science and Engineering, Fuzhou University, Fuzhou, Fujian, China.
  • Houbing Zheng
    Department of Plastic and Cosmetic Surgery, the First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Jialin Ye
    College of Biological Science and Engineering, Fuzhou University, Fuzhou, Fujian, China.
  • Meihua Zhou
    The Center for Big Data Research in Burns and Trauma, College of Computer and Data Science/College of Software, Fuzhou University, Fujian, China.
  • Haisu Zheng
    College of Biological Science and Engineering, Fuzhou University, Fuzhou, Fujian, China.
  • Yongqiang Yu
    College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China.
  • Yi Zhong
    Department of Chinese Medicine Science & Engineering,Zhejiang University Hangzhou 310058,China.
  • Yuanzi Wu
    College of Biological Science and Engineering, Fuzhou University, Fuzhou, Fujian, China.
  • Da Huang
    College of Biological Science and Engineering, Fuzhou University, Fuzhou, Fujian, China.
  • Biao Wang
    School of Electronic Information, Jiangsu University of Science and Technology, Zhenjiang 212100, China.
  • Zuquan Weng
    The Centre for Big Data Research in Burns and Trauma, Fuzhou University, Fujian Province, China.