{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-10529451","patent":{"patent_number":"US-10529451","title":"PINS: a perturbation clustering approach for data integration and disease subtyping","assignee":null,"inventors":[],"filing_date":"2016-03-11T00:00:00.000Z","publication_date":"2020-01-07T00:00:00.000Z","cpc_codes":["G16H","G06F","G16H"],"num_claims":1,"abstract":"Disease subtyping is accomplished by a computer-implemented algorithm that manipulates a first genetic dataset to construct a set of first connectivity matrices. To this set of matrices Gaussian noise is introduced to generate a perturbed dataset. The computer-implemented algorithm assesses which of the set of first connectivity matrices was least affected by introduction of noise and that matric is used to define the optimal clustering. Once the optimal clustering is determined, computer-implemented supervised classification is performed to determine, for a particular patient, with which disease subtype cluster that person's genetic data most closely aligns. Armed with this knowledge, the treatment regimen is specified with much higher likelihood of success."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"PINS: a perturbation clustering approach for data integration and disease subtyping","description":"Disease subtyping is accomplished by a computer-implemented algorithm that manipulates a first genetic dataset to construct a set of first connectivity matrices. To this set of matrices Gaussian noise","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-10529451","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-10529451","citation_suggestion":"Patentable. \"PINS: a perturbation clustering approach for data integration and disease subtyping\" (US-10529451). https://patentable.app/patents/US-10529451","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-10529451","json":"https://patentable.app/api/llm-context/US-10529451","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T13:41:35.330Z"}