proteins and gene regulatory networks regulate homeostasis, response to stress, and the emergence of complex traits, and their structure and dynamics encode function. we use machine learning and simulations to probe this relationship across scales, from single molecules to whole transcriptomes across millions of single cells

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rare behavior in noisy complex biophysical systems can be regulated and it's mechanism inferred by tunable control knobs. we use ai models to probe and parameterize these knobs with generative models, studying molecular and cellular processes that often exhibit emergent, collective action  

resistant cancer cells undergo clonal expansion to proliferate in new environments and even in the presence of targeted drugs. we learn how to steer these processes and the groups of genes that cause them