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Unravelling the eukaryotic post-transcriptional regulatory code

CORDIS · observation · Publication date unknown

elechano) to probe post-transcriptional regulation at an unprecedented scale across a broad range of species and conditions with synthetic biology to massively test regulatory sequences (Verstrepen). Deep learning on these data allows us to build predictive models and unravel complex regulatory instructions (Gagneur). Ultimately, EPIC will enable us to decipher the actual language of gene regulation and facilitate (re)writing genomes. EPIC will enable understanding and predicting regulation, and ultimately phenotype, from DNA, closing a major gap in basic biology, while also opening exciting avenues for applications in biotechnology and medicine, from pinpointing disease-causing mutations to rational design of genes, RNAs and cells. post-transcriptional regulation; deep learning; RNA biology; yeast; microbiology; synthetic biology

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recordType

award

status

SIGNED

region

EU

value

9989247

unit

EUR