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.

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.

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.

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.