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    MACHINE LEARNING FOR PROTEIN BINDING SITES
    45.
    发明公开
    MACHINE LEARNING FOR PROTEIN BINDING SITES 审中-实审

    公开(公告)号：EP4354447A3

    公开(公告)日：2024-06-19

    申请号：EP24160073.3

    申请日：2019-11-29

    申请人： BenevolentAI Technology Limited

    发明人： MEYERS, Joshua ,  SEGLER, Marwin ,  SIMONOVSKY, Martin

    IPC分类号： G16B15/30 ,  G16B40/20

    CPC分类号： G16B15/30 ,  G16B40/20

    摘要： A computer-implemented method of training a machine learning model to learn ligand binding similarities between protein binding sites is disclosed. The method comprises inputting to the machine learning model: a representation of a first binding site; a representation of a second binding site, wherein the representations of the first and second binding sites comprise structural information; and a label comprising an indication of ligand binding similarity between the first binding site and the second binding site. The method also comprises outputting from the machine model a similarity indicator based on the representations of the first and second binding sites; performing a comparison between the similarity indicator and the label; and updating the machine learning model based on the comparison.

    APPARATUS AND METHOD FOR PREDICTING CELL TYPE ENRICHMENT FROM TISSUE IMAGES USING SPATIALLY RESOLVED GENE EXPRESSION DATA
    49.
    发明公开
    APPARATUS AND METHOD FOR PREDICTING CELL TYPE ENRICHMENT FROM TISSUE IMAGES USING SPATIALLY RESOLVED GENE EXPRESSION DATA 审中-公开

    公开(公告)号：EP4325505A1

    公开(公告)日：2024-02-21

    申请号：EP22788243.8

    申请日：2022-02-14

    申请人： Portrai Inc.

    发明人： CHOI, Hongyoon ,  KIM, Young Tae ,  NA, Kwon Joong

    IPC分类号： G16B15/30 ,  G16C20/30 ,  G16B40/20

    摘要： An apparatus for predicting cell type enrichment from tissue images using spatially resolved gene expression data comprises: a communication module for receiving tissue images of a test object; memory in which a program for predicting cell type enrichment information from the tissue images is stored; and a processor for executing the program. The program predicts the cell type enrichment information by inputting the tissue images to a cell type enrichment prediction model trained on the basis of training data composed of spatially resolved transcriptome information and tissue images spatially matched to the spatially resolved transcriptome information. The spatially resolved transcriptome information includes: transcriptome data including spatial information; and tissue image data sharing the spatial information. The spatial information refers to position information about a plurality of spots arranged as a two-dimensional plane in the tissue image data, and includes the coordinates of each of the spots.