{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11515010","patent":{"patent_number":"US-11515010","title":"Deep convolutional neural networks to predict variant pathogenicity using three-dimensional (3D) protein structures","assignee":null,"inventors":[],"filing_date":"2021-09-07T00:00:00.000Z","publication_date":"2022-11-29T00:00:00.000Z","cpc_codes":["G16B","G06N","G06N","G06N","G06N","G16B","G16B","G16B","G06N","G06N"],"num_claims":30,"abstract":"The technology disclosed relates to determining pathogenicity of variants. In particular, the technology disclosed relates to generating amino acid-wise distance channels for a plurality of amino acids in a protein. Each of the amino acid-wise distance channels has voxel-wise distance values for voxels in a plurality of voxels. A tensor includes the amino acid-wise distance channels and at least an alternative allele of the protein expressed by a variant. A deep convolutional neural network determines a pathogenicity of the variant based at least in part on processing the tensor. The technology disclosed further augments the tensor with supplemental information like a reference allele of the protein, evolutionary conservation data about the protein, annotation data about the protein, and structure confidence data about the protein."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Deep convolutional neural networks to predict variant pathogenicity using three-dimensional (3D) protein structures","description":"The technology disclosed relates to determining pathogenicity of variants. In particular, the technology disclosed relates to generating amino acid-wise distance channels for a plurality of amino acid","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11515010","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11515010","citation_suggestion":"Patentable. \"Deep convolutional neural networks to predict variant pathogenicity using three-dimensional (3D) protein structures\" (US-11515010). https://patentable.app/patents/US-11515010","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11515010","json":"https://patentable.app/api/llm-context/US-11515010","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T00:36:03.898Z"}