Patents by Inventor Avantika LAL

Avantika LAL 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).

  • Genetic mutation detection using deep learning
    Patent number: 12094572
    Abstract: The present disclosure provides methods, systems, and computer program products that use deep learning models to classify candidate mutations detected in sequencing data, particularly suboptimal sequencing data. The methods, systems, and programs provide for increased efficiency, accuracy, and speed in identifying mutations from a wide range of sequencing data.
    Type: Grant
    Filed: August 5, 2022
    Date of Patent: September 17, 2024
    Assignee: NVIDIA Corporation
    Inventors: Johnny Israeli, Avantika Lal, Michael Vella, Nikolai Yakovenko, Zhen Hu
  • Genetic mutation detection using deep learning
    Patent number: 11443832
    Abstract: The present disclosure provides methods, systems, and computer program products that use deep learning models to classify candidate mutations detected in sequencing data, particularly suboptimal sequencing data. The methods, systems, and programs provide for increased efficiency, accuracy, and speed in identifying mutations from a wide range of sequencing data.
    Type: Grant
    Filed: March 7, 2019
    Date of Patent: September 13, 2022
    Assignee: NVIDIA Corporation
    Inventors: Johnny Israeli, Avantika Lal, Michael Vella, Nikolai Yakovenko, Zhen Hu
  • SEQUENCE VARIATION DETECTION USING DEEP LEARNING
    Publication number: 20200365234
    Abstract: The present disclosure provides methods, systems, and computer program products that use embeddings of candidate variation information and deep learning models to accurately and efficiently detect variations in biopolymer sequencing data, particularly suboptimal sequencing data.
    Type: Application
    Filed: May 13, 2019
    Publication date: November 19, 2020
    Applicant: NVIDIA Corporation
    Inventors: Nikolai YAKOVENKO, Johnny ISRAELI, Avantika LAL, Michael VELLA, Zhen HU
  • GENETIC MUTATION DETECTION USING DEEP LEARNING
    Publication number: 20200286587
    Abstract: The present disclosure provides methods, systems, and computer program products that use deep learning models to classify candidate mutations detected in sequencing data, particularly suboptimal sequencing data. The methods, systems, and programs provide for increased efficiency, accuracy, and speed in identifying mutations from a wide range of sequencing data.
    Type: Application
    Filed: March 7, 2019
    Publication date: September 10, 2020
    Applicant: NVIDIA Corporation
    Inventors: Johnny ISRAELI, Avantika LAL, Michael VELLA, Nikolai YAKOVENKO, Zhen HU