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Designing Protein Structures from Natural Language

Paper recorded by Signals 4 on 2026-10-09 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-09 on arXiv · recorded by Signals 4 on 2026-10-12

Category: cs.LG · 机器学习 · first seen 2026-10-12

Abstract

A central challenge in de novo protein design is generating proteins with desired structural and functional properties. Existing design models typically require a dedicated input representation for each property, limiting the design objectives they support. We develop Prompteina, the first all-atom structure generation model that supports new and broader design objectives specified in natural lang

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#302 most recent of 749 cs.LG papers we have recorded · ↑ newer: DyssomniaNN: Multi-Scale Spiking Neural Modeling of Human Sleep Disord · ↓ older: Hitting-Time Bounds for Asynchronous Q-Learning
Cite this page: Designing Protein Structures from Natural Language: the #302 most recent of 749 cs.LG papers we have recorded (as of 2026-10-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/designing-protein-structures-from-natural-language.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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