[Drug repositioning prediction based on dynamic feature learning on heterogeneous graphs].

Haokun Zhu1, Yanbu Guo1,2, Xiangjun Xin1

  • 1School of Software Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, China.

Summary

This study introduces a new artificial intelligence method for drug repositioning prediction using dynamic representation learning on heterogeneous biological networks. The novel approach effectively models complex biological relationships, improving prediction accuracy for complex diseases.

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