Patents by Inventor Brandi CANTAREL

Brandi CANTAREL 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).

  • METHOD OF MACHINE LEARNING, EMPLOYING BAYESIAN LATENT CLASS INFERENCE: COMBINING MULTIPLE GENOMIC FEATURE DETECTION ALGORITHMS TO PRODUCE AN INTEGRATED GENOMIC FEATURE SET WITH SPECIFICITY, SENSITIVITY AND ACCURACY
    Publication number: 20210174907
    Abstract: BAYSIC (BAYesian System for Integrated Combination) combines sets of genomic and other biological data features to optimize selected data feature attributes, for example, detecting genome variants including single nucleotide variants (SNVs) and small insertion/deletions in genomes. The present disclosure presents one possible embodiment employing BAYSIC to combine single nucleotide variants detected by several distinct variant calling methods into an integrated SNV call set that is more accurate than any single SNV calling method or any ad hoc method of combining call sets. BAYSIC is a, tested and validated method using unsupervised machine learning, employing Bayesian latent class inference to combine variant sets produced by different packages.
    Type: Application
    Filed: July 10, 2020
    Publication date: June 10, 2021
    Inventors: Aaron J. MACKEY, Brandi CANTAREL, Justin REESE, Daniel B. WEAVER
  • METHOD OF MACHINE LEARNING, EMPLOYING BAYESIAN LATENT CLASS INFERENCE: COMBINING MULTIPLE GENOMIC FEATURE DETECTION ALGORITHMS TO PRODUCE AN INTEGRATED GENOMIC FEATURE SET WITH SPECIFICITY, SENSITIVITY AND ACCURACY
    Publication number: 20140143188
    Abstract: BAYSIC (BAYesian System for Integrated Combination) combines sets of genomic and other biological data features to optimize selected data feature attributes, for example, detecting genome variants including single nucleotide variants (SNVs) and small insertion/deletions in genomes. The present disclosure presents one possible embodiment employing BAYSIC to combine single nucleotide variants detected by several distinct variant calling methods into an integrated SNV call set that is more accurate than any single SNV calling method or any ad hoc method of combining call sets. BAYSIC is a, tested and validated method using unsupervised machine learning, employing Bayesian latent class inference to combine variant sets produced by different packages.
    Type: Application
    Filed: November 18, 2013
    Publication date: May 22, 2014
    Applicant: GENFORMATIC, LLC
    Inventors: Aaron J. MACKEY, Brandi CANTAREL, Justin REESE, Daniel B. WEAVER