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filingDate 2022-04-14-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_47a066600f06f48c4b8dd3ecbbf1925a
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publicationDate 2022-10-20-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber WO-2022221591-A1
titleOfInvention Multi-channel protein voxelization to predict variant pathogenicity using deep convolutional neural networks
abstract A system includes at least a voxelizer, an alternative allele encoder, an evolutionary conservation encoder, and a convolutional neural network. The voxelizer accesses a three-dimensional structure of a reference amino acid sequence of a protein and fits a three-dimensional grid of voxels on atoms in the three-dimensional structure on an amino acid-basis to generate amino acid-wise distance channels. The alternative allele encoder encodes an alternative allele sequence to each voxel in the three-dimensional grid of voxels. The evolutionary conservation encoder encodes an evolutionary conservation sequence to each voxel in the three-dimensional grid of voxels. The convolutional neural network applies three-dimensional convolutions to a tensor that includes the amino acid-wise distance channels encoded with the alternative allele sequence and respective evolutionary conservation sequences and determines a pathogenicity of a variant nucleotide based at least in part on the tensor.
priorityDate 2021-04-15-04:00^^<http://www.w3.org/2001/XMLSchema#date>
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