Patents by Inventor Rachid Ounit

Rachid Ounit 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).

Systems and methods for ultra-fast identification and abundance estimates of microorganisms using a kmer-depth based approach and privacy-preserving protocols

Patent number: 12176071

Abstract: The present disclosure relates to the use of next generation technologies and analysis using a k-mer based approach which is depth-informed to classify microorganism and estimate abundance in single or mixed microorganismal populations in a rapid manner. The disclosure relates to methods for identifying taxa from environmentally or patient collected samples and processing these samples in a privacy-preserving manner.

Type: Grant

Filed: October 26, 2016

Date of Patent: December 24, 2024

Assignee: The Joan & Irwin Jacobs Technion-Cornell Institute

Inventors: Niamh B. O'Hara, Rachid Ounit
SYSTEMS AND METHODS FOR ULTRA-FAST IDENTIFICATION AND ABUNDANCE ESTIMATES OF MICROORGANISMS USING A KMER-DEPTH BASED APPROACH AND PRIVACY-PRESERVING PROTOCOLS

Publication number: 20190318807

Abstract: The present disclosure relates to the use of next generation technologies and analysis using a k-mer based approach which is depth-informed to classify microorganism and estimate abundance in single or mixed microorganismal populations in a rapid manner. The disclosure relates to methods for identifying taxa from environmentally or patient collected samples and processing these samples in a privacy-preserving manner.

Type: Application

Filed: October 26, 2016

Publication date: October 17, 2019

Inventors: Niamh B. O'Hara, Rachid Ounit

Systems and methods for ultra-fast identification and abundance estimates of microorganisms using a kmer-depth based approach and privacy-preserving protocols

SYSTEMS AND METHODS FOR ULTRA-FAST IDENTIFICATION AND ABUNDANCE ESTIMATES OF MICROORGANISMS USING A KMER-DEPTH BASED APPROACH AND PRIVACY-PRESERVING PROTOCOLS