Patents by Inventor Sitharthan Kalalakaran

Sitharthan Kalalakaran has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Diagnostic genetic analysis using variant-disease association with patient-specific relevance assessment
    Patent number: 10679726
    Abstract: Relevance of a study genetic variant observed in diagnostic subject genetic data that is associated by a clinical study with a phenotype characteristic is assessed as follows. A set of polymorphisms functionally related to the study genetic variant are identified. A foreground distribution is computed of variants observed in the diagnostic subject genetic data for the set of polymorphisms. A background distribution is computed of variants observed in genetic data of subjects of the clinical study for the set of polymorphisms. A comparison metric is computed comparing the foreground distribution and the background distribution. Relevance of the study variant to the diagnostic subject is quantified based on the comparison metric, with higher similarity of the foreground and background distributions corresponding to higher relevance.
    Type: Grant
    Filed: November 15, 2013
    Date of Patent: June 9, 2020
    Assignee: Koninklijke Philips N.V.
    Inventors: Sitharthan Kalalakaran, Vinay Varadan, Nilanjana Banerjee, Angel Janevski, Nevenka Dimitrova
  • DIAGNOSTIC GENETIC ANALYSIS USING VARIANT-DISEASE ASSOCIATION WITH PATIENT-SPECIFIC RELEVANCE ASSESSMENT
    Publication number: 20150294063
    Abstract: Relevance of a study genetic variant observed in diagnostic subject genetic data that is associated by a clinical study with a phenotype characteristic is assessed as follows. A set of polymorphisms functionally related to the study genetic variant are identified. A foreground distribution is computed of variants observed in the diagnostic subject genetic data for the set of polymorphisms. A background distribution is computed of variants observed in genetic data of subjects of the clinical study for the set of polymorphisms. A comparison metric is computed comparing the foreground distribution and the background distribution. Relevance of the study variant to the diagnostic subject is quantified based on the comparison metric, with higher similarity of the foreground and background distributions corresponding to higher relevance.
    Type: Application
    Filed: November 15, 2013
    Publication date: October 15, 2015
    Applicant: KONINKLIJKE PHILIPS N.V.
    Inventors: Sitharthan Kalalakaran, Vinay Varadan, Nilanjana Banerjee, Angel Janevski, Nevenka Dimitrova