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PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data.

Jie HaoYoungsoon KimTae-Kyung KimMingon Kang
Published in: BMC bioinformatics (2018)
PASNet can describe the different biological systems of clinical outcomes for prognostic prediction as well as predicting prognosis more accurately than the current state-of-the-art methods. PASNet is the first pathway-based deep neural network that represents hierarchical representations of genes and pathways and their nonlinear effects, to the best of our knowledge. Additionally, PASNet would be promising due to its flexible model representation and interpretability, embodying the strengths of deep learning. The open-source code of PASNet is available at https://github.com/DataX-JieHao/PASNet .
Keyphrases
  • neural network
  • high throughput
  • deep learning
  • healthcare
  • working memory
  • genome wide
  • electronic health record
  • single cell
  • genome wide identification
  • bioinformatics analysis
  • solid state