Methods and compositions for applying machine learning to plant biotechnology

    公开(公告)号:US12131806B2

    公开(公告)日:2024-10-29

    申请号:US18208207

    申请日:2023-06-09

    CPC classification number: G16B40/00 C12N5/04 G06N3/044 G06N3/047 G16H50/20

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using machine learning models for plant biotechnology. One of the methods includes obtaining a network input comprising an image depicting a plurality of plant cells or regions of plant tissue; processing the network input using a machine learning model to obtain an identification of one or more particular biotechnologically-modifiable plant cells or one or more particular biotechnologically-modifiable regions of the plant tissue; excising or delineating the one or more identified plant cells or the one or more identified regions of the plant tissue; and delivering exogenous material to the excised or delineated plant cells or regions of plant tissue.

    Methods and compositions for applying machine learning to plant biotechnology

    公开(公告)号:US11763916B1

    公开(公告)日:2023-09-19

    申请号:US16853297

    申请日:2020-04-20

    CPC classification number: G16B40/00 C12N5/04 G06N3/044 G06N3/047 G16H50/20

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using machine learning models for plant biotechnology. One of the methods includes obtaining a network input comprising an image depicting a plurality of plant cells or regions of plant tissue; processing the network input using a machine learning model to obtain an identification of one or more particular biotechnologically-modifiable plant cells or one or more particular biotechnologically-modifiable regions of the plant tissue; excising or delineating the one or more identified plant cells or the one or more identified regions of the plant tissue; and delivering exogenous material to the excised or delineated plant cells or regions of plant tissue.

    METHODS AND COMPOSITIONS FOR APPLYING MACHINE LEARNING TO PLANT BIOTECHNOLOGY

    公开(公告)号:US20230317210A1

    公开(公告)日:2023-10-05

    申请号:US18208207

    申请日:2023-06-09

    CPC classification number: G16B40/00 C12N5/04 G06N3/044 G06N3/047 G16H50/20

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using machine learning models for plant biotechnology. One of the methods includes obtaining a network input comprising an image depicting a plurality of plant cells or regions of plant tissue; processing the network input using a machine learning model to obtain an identification of one or more particular biotechnologically-modifiable plant cells or one or more particular biotechnologically-modifiable regions of the plant tissue; excising or delineating the one or more identified plant cells or the one or more identified regions of the plant tissue; and delivering exogenous material to the excised or delineated plant cells or regions of plant tissue.

    Methods and compositions for governing phenotypic outcomes in plants

    公开(公告)号:US11908547B2

    公开(公告)日:2024-02-20

    申请号:US16870838

    申请日:2020-05-08

    CPC classification number: G16B20/00 G06N5/04 G06N20/00 G16B40/00 G06Q50/02

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for governing phenotypic outcomes in plants. One method includes obtaining a model input comprising time series data, wherein the time series data comprises, for each previous time point of one or more previous time points, at least one of i) first multi-omics data corresponding to a plant at the previous time point, or ii) phenotypic data corresponding to the plant at the previous time point; and processing the model input using a machine learning model to obtain a model output that comprises, for each future time point of one or more of future time points, a prediction of at least one of i) a phenotype of the plant at the future time point, or ii) second multi-omics data corresponding to the plant at the future time point.

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