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DeepNetBim: deep learning model for predicting HLA-epitope interactions based on network analysis by harnessing binding and immunogenicity information.

Xiaoyun YangLiyuan ZhaoFang WeiJing Li
Published in: BMC bioinformatics (2021)
We developed a network-based deep learning method called DeepNetBim as a pan-specific epitope prediction tool. It extracted the attributes of the network as new features from HLA-peptide binding and immunogenic models. We observed that not only did DeepNetBim binding model outperform other updated methods but the combination of our two models showed better performance. This indicates further applications in clinical practice.
Keyphrases
  • network analysis
  • deep learning
  • clinical practice
  • dna binding
  • artificial intelligence
  • binding protein
  • convolutional neural network
  • machine learning
  • monoclonal antibody
  • big data
  • healthcare