GraphLoc: a graph neural network model for predicting protein subcellular localization from immunohistochemistry images.

Journal: Bioinformatics (Oxford, England)
PMID: 36111875

Abstract

MOTIVATION: Recognition of protein subcellular distribution patterns and identification of location biomarker proteins in cancer tissues are important for understanding protein functions and related diseases. Immunohistochemical (IHC) images enable visualizing the distribution of proteins at the tissue level, providing an important resource for the protein localization studies. In the past decades, several image-based protein subcellular location prediction methods have been developed, but the prediction accuracies still have much space to improve due to the complexity of protein patterns resulting from multi-label proteins and the variation of location patterns across cell types or states.

Authors

  • Jin-Xian Hu
    Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.
  • Yang Yang
    Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
  • Ying-Ying Xu
  • Hong-Bin Shen
    Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China. hbshen@sjtu.edu.cn.

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