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also opens new avenues for the design of climate-resilient crops. You will apply AI strategies to learn the regulatory syntax encoded by the Arabidopsis genome using single-cell transcript data as
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and ultimately accelerate these activities to combat climate change. Our approach combines science and engineering, beginning with the study of fundamental microbial metabolic processes that can be
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the fundamental aspects of transcriptional control, this project also opens new avenues for the design of climate-resilient crops. Supported by single-cell profiling and predictive artificial intelligence models
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temperature signalling in plants, such as the model plant Arabidopsis thaliana and the crop plants wheat and soybean. To unravel this, we focus on dynamic changes in protein phosphorylation status, since