Generative modeling of intrinsically disordered protein regions by reinforcing sparse autoencoder features
Paper recorded by Signals 4 on 2026-10-01 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-01 on arXiv · recorded by Signals 4 on 2026-10-02
Category: cs.LG · 机器学习 · first seen 2026-10-02
Abstract
Intrinsically disordered protein regions (IDRs) play central roles in cellular processes such as transcriptional regulation, signal transduction, and subcellular localization, yet their functional design remains challenging. Structure-based design methods do not readily apply to IDRs, and existing protein language models are trained on full-length protein sequences, thus learning a prior that is b
Read on arXiv →
Cite this page: Generative modeling of intrinsically disordered protein regions by reinforcing sparse autoencoder features: the #6 most recent of 362 cs.LG papers we have recorded (as of 2026-10-01). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/generative-modeling-of-intrinsically-disordered-protein-regions-by-reinforcing-s.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable:
papers.json
Get 4 AI signals a day by email — free.
Get 4 AI signals a day by email — free