Corpus ID: 160017948

Generative Models for Graph-Based Protein Design

@inproceedings{Ingraham2019GenerativeMF,
  title={Generative Models for Graph-Based Protein Design},
  author={John Ingraham and Vikas K. Garg and R. Barzilay and T. Jaakkola},
  booktitle={DGS@ICLR},
  year={2019}
}

• John Ingraham, Vikas K. Garg, +1 author T. Jaakkola
• Published in DGS@ICLR 2019
• Computer Science

Engineered proteins offer the potential to solve many problems in biomedicine, energy, and materials science, but creating designs that succeed is difficult in practice. [...] Key Method Our approach efficiently captures the complex dependencies in proteins by focusing on those that are long-range in sequence but local in 3D space. Our framework improves in both speed and reliability over conventional and neural network-based approaches, and takes a step toward rapid and targeted biomolecular design with the…Expand

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