Interpretable and generative deep learning models explicate phase separating intrinsically disordered motifs.

Abstract excerpt

Intrinsically disordered regions (IDRs) in proteins drive phase separation (PS) to form biomolecular condensates, which organize cellular matter. While IDRs are recognized as critical drivers of PS, the systematic identification of sequence motifs governing this phenomenon and their compositional determinants remain a key challenge. Here we develop PhaSeMotif, a deep learning framework for interpretable and...

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