arXiv Machine Learning
Sep 23

MT-ProtBERT: Multi-task Learning ProtBERT for Intrinsically Disordered Proteins Classification with Scarce Data

MT-ProtBERT is a multi‑task extension of ProtBERT designed for classifying intrinsically disordered proteins (IDPs) in low‑data settings. It combines Dynamic Window Masking, a Multi‑Scale 1D Convolutional classifier, and auxiliary biochemistry‑informed objectives to jointly optimize masked language modeling and domain‑specific tasks. In experiments on phosphorylation site prediction and protein compaction prediction, MT‑ProtBERT outperforms the RNN‑based IDP model PARROT across all limited‑data tasks.

By Jian Sun, Kingshuk Ghosh, Lilianna Houston, Mohammad H. Mahoor