Congratulations to Bernardo, Fanny, Michi and Alex on their new paper now published in Nature Genetics! DeepSTARR is a deep-learning model that is able to quantitatively predict the activities of enhancers directly from DNA sequence. Their model learned cis-regulatory rules that further allowed them to design synthetic de novo enhancers with desired activities.
Read an interview with the authors.
de Almeida B. P., Reiter F., Pagani M., Stark A. DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers. Nature Genetics, May 2022
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