Patents by Inventor Brian Trippe

Brian Trippe 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).

  • NEURAL NETWORK FOR PROCESSING APTAMER DATA
    Publication number: 20240006027
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for obtaining data defining a sequence for an aptamer, the aptamer comprising a string of nucleobases; encoding the data defining the sequence for the aptamer as a neural network input; and processing the neural network input using a neural network to generate an output that characterizes how strongly the aptamer binds to a particular target molecule, wherein the neural network has been configured through training to receive the data defining the sequence and to process the data to generate predicted outputs that characterize how strongly the aptamer binds to the particular target molecule.
    Type: Application
    Filed: April 26, 2023
    Publication date: January 4, 2024
    Inventors: Michelle Therese Hoerner Dimon, Marc Berndl, Marc Adlai Coram, Brian Trippe, Patrick F. Riley, Philip Charles Nelson
  • Neural network for processing aptamer data
    Patent number: 11670400
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for obtaining data defining a sequence for an aptamer, the aptamer comprising a string of nucleobases; encoding the data defining the sequence for the aptamer as a neural network input; and processing the neural network input using a neural network to generate an output that characterizes how strongly the aptamer binds to a particular target molecule, wherein the neural network has been configured through training to receive the data defining the sequence and to process the data to generate predicted outputs that characterize how strongly the aptamer binds to the particular target molecule.
    Type: Grant
    Filed: January 24, 2020
    Date of Patent: June 6, 2023
    Assignee: Google LLC
    Inventors: Michelle Therese Hoerner Dimon, Marc Berndl, Marc Adlai Coram, Brian Trippe, Patrick F. Riley, Philip Charles Nelson
  • NEURAL NETWORK FOR PROCESSING APTAMER DATA
    Publication number: 20200160937
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for obtaining data defining a sequence for an aptamer, the aptamer comprising a string of nucleobases; encoding the data defining the sequence for the aptamer as a neural network input; and processing the neural network input using a neural network to generate an output that characterizes how strongly the aptamer binds to a particular target molecule, wherein the neural network has been configured through training to receive the data defining the sequence and to process the data to generate predicted outputs that characterize how strongly the aptamer binds to the particular target molecule.
    Type: Application
    Filed: January 24, 2020
    Publication date: May 21, 2020
    Inventors: Michelle Therese Hoerner Dimon, Marc Berndl, Marc Adlai Coram, Brian Trippe, Patrick F. Riley, Philip Charles Nelson
  • Neural network for processing aptamer data
    Patent number: 10546650
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for obtaining data defining a sequence for an aptamer, the aptamer comprising a string of nucleobases; encoding the data defining the sequence for the aptamer as a neural network input; and processing the neural network input using a neural network to generate an output that characterizes how strongly the aptamer binds to a particular target molecule, wherein the neural network has been configured through training to receive the data defining the sequence and to process the data to generate predicted outputs that characterize how strongly the aptamer binds to the particular target molecule.
    Type: Grant
    Filed: October 23, 2015
    Date of Patent: January 28, 2020
    Assignee: Google LLC
    Inventors: Michelle Therese Hoerner Dimon, Marc Berndl, Marc Adlai Coram, Brian Trippe, Patrick F. Riley, Philip Charles Nelson
  • NEURAL NETWORK FOR PROCESSING APTAMER DATA
    Publication number: 20170116371
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for obtaining data defining a sequence for an aptamer, the aptamer comprising a string of nucleobases; encoding the data defining the sequence for the aptamer as a neural network input; and processing the neural network input using a neural network to generate an output that characterizes how strongly the aptamer binds to a particular target molecule, wherein the neural network has been configured through training to receive the data defining the sequence and to process the data to generate predicted outputs that characterize how strongly the aptamer binds to the particular target molecule.
    Type: Application
    Filed: October 23, 2015
    Publication date: April 27, 2017
    Applicant: GOOGLE INC.
    Inventors: Michelle Therese Hoerner Dimon, Marc Berndl, Marc Adlai Coram, Brian Trippe, Patrick F. Riley, Philip Charles Nelson