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Protein Solvent-Accessibility Prediction by a Stacked Deep Bidirectional Recurrent Neural Network
2018
Biomolecules
Residue solvent accessibility is closely related to the spatial arrangement and packing of residues. Predicting the solvent accessibility of a protein is an important step to understand its structure and function. In this work, we present a deep learning method to predict residue solvent accessibility, which is based on a stacked deep bidirectional recurrent neural network applied to sequence profiles. To capture more long-range sequence information, a merging operator was proposed when
doi:10.3390/biom8020033
pmid:29799510
pmcid:PMC6023031
fatcat:sfpel3ts3jeybd3egswqefv7yu