TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

Zixuan Cang Michigan State University Guo-Wei Wei Michigan State University

Data Analysis, Bio-Statistics, Bio-Mathematics mathscidoc:1904.42007

PLOS Computational Biology, 13, (7), e1005690, 2017.7
Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/
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@inproceedings{zixuan2017topologynet:,
  title={TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions},
  author={Zixuan Cang, and Guo-Wei Wei},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20190430004113193029292},
  booktitle={PLOS Computational Biology},
  volume={13},
  number={7},
  pages={e1005690},
  year={2017},
}
Zixuan Cang, and Guo-Wei Wei. TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions. 2017. Vol. 13. In PLOS Computational Biology. pp.e1005690. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20190430004113193029292.
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