Bidirectional Long Short-Term Memory Networks for Predicting the Subcellular Localization of Eukaryotic Proteins

@article{Thireou2007BidirectionalLS,
  title={Bidirectional Long Short-Term Memory Networks for Predicting the Subcellular Localization of Eukaryotic Proteins},
  author={T. Thireou and M. Reczko},
  journal={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
  year={2007},
  volume={4}
}
  • T. Thireou, M. Reczko
  • Published 2007
  • Computer Science, Medicine
  • IEEE/ACM Transactions on Computational Biology and Bioinformatics
An algorithm called bidirectional long short-term memory networks (BLSTM) for processing sequential data is introduced. This supervised learning method trains a special recurrent neural network to use very long-range symmetric sequence context using a combination of nonlinear processing elements and linear feedback loops for storing long-range context. The algorithm is applied to the sequence-based prediction of protein localization and predicts 93.3 percent novel nonplant proteins and 88.4… Expand
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