Predicting Synthetic Lethality in Human Cancers via Multi-Graph Ensemble Neural Network

Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov:2021:1731-1734. doi: 10.1109/EMBC46164.2021.9630716.

Abstract

Synthetic lethality (SL) is currently one of the most effective methods to identify new drugs for cancer treatment. It means that simultaneous inactivation target of two non-lethal genes will cause cell death, but loss of either will not. However, detecting SL pair is challenging due to the experimental costs. Artificial intelligence (AI) is a low-cost way to predict the potential SL relation between two genes. In this paper, a new Multi-Graph Ensemble (MGE) network structure combining graph neural network and existing knowledge about genes is proposed to predict SL pairs, which integrates the embedding of each feature with different neural networks to predict if a pair of genes have SL relation. It has a higher prediction performance compared with existing SL prediction methods. Also, with the integration of other biological knowledge, it has the potential of interpretability.

MeSH terms

  • Artificial Intelligence
  • Humans
  • Neoplasms* / genetics
  • Neural Networks, Computer
  • Synthetic Lethal Mutations* / genetics