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Multi-task learning uncovers robust translation cis-regulatory features

ABSTRACT: To validate the sequence motifs identified by our multi-task learning model MTtrans, a new 5' UTR library with around 8,000 synthetic 5'UTRs was built to express EGFP. The reads count was used as a proxy of translation rate here to validate the estimated regulatory effect of motifs that we inferred from multiple datasets, proving the robustness of the sequence motifs.

ORGANISM(S): Homo sapiens

PROVIDER: GSE201766 | GEO | 2022/04/28

REPOSITORIES: GEO

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