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    PATHOLOGY PREDICTION BASED ON SPATIAL FEATURE ANALYSIS
    133.
    发明公开
    PATHOLOGY PREDICTION BASED ON SPATIAL FEATURE ANALYSIS 审中-公开

    公开(公告)号：US20230143860A1

    公开(公告)日：2023-05-11

    申请号：US17986737

    申请日：2022-11-14

    Applicant: Genentech, Inc. ,  Hoffmann-La Roche Inc.

    Inventor： Xiao LI ,  Jian DAI ,  Fabien GAIRE

    IPC: G06T7/00 ,  G16H50/20 ,  G06V20/69

    CPC classification number: G06T7/0012 ,  G16H50/20 ,  G06V20/698 ,  G06T2207/10024 ,  G06T2207/10056 ,  G06T2207/30096

    Abstract: Systems and methods relate to processing digital pathology mages. More specifically, depictions of objects of a first class (e.g., lymphocytes) and depictions of objects of a second class (e.g., tumor cells) are detected. Locations of each biological object depiction are identified, which are used to generate multiple spatial-distribution metrics that characterize where depictions of objects of a first class are located relative to objects of a second class. The spatial-distribution metrics are used to generate a result corresponding to a predicted biological state of or a potential treatment of a subject. For example, the result may predict whether and/or an extent to which lymphocytes have infiltrated a tumor, whether checkpoint blockade therapy would be an effective treatment for the subject, and/or whether a subject is eligible for a clinical trial.

    PREDICTION OF PEPTIDE CLEAVAGE IN POLYPEPTIDES THROUGH PHYSICS-BASED SIMULATIONS
    138.
    发明申请
    PREDICTION OF PEPTIDE CLEAVAGE IN POLYPEPTIDES THROUGH PHYSICS-BASED SIMULATIONS 有权

    公开(公告)号：US20230120018A1

    公开(公告)日：2023-04-20

    申请号：US18058110

    申请日：2022-11-22

    Applicant: Genentech, Inc.

    Inventor： Karthikan Rajagopal ,  Nisana Marie Andersen ,  Saeed Izadi ,  Robert Franklin Kelley, JR.

    IPC: G16B15/20 ,  G16B40/20 ,  G06N7/01

    Abstract: The present disclosure relates to polypeptide degradation, and in particular to techniques for predicting the likelihood that a peptide bond for a given polypeptide molecule is susceptible to a cleavage reaction. Particularly, aspects of the present disclosure are directed to generating a representation of a polypeptide, performing a molecular-dynamics simulation using the representation to obtain a set of polypeptide conformations, determining, for each polypeptide conformation, a spatial characteristic of an amino acid, estimating a nucleophilic attack distance of each polypeptide conformation based on the spatial characteristic, identifying a reactive conformation that is susceptible to a cleavage reaction based on the nucleophilic attack distance of each polypeptide conformation, determining a free energy of the spatial characteristic of the amino acid in the reactive conformation; and predicting a probability of the side chain of the amino acid being trapped in the reactive conformation based on the free energy.

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