Metraipolis › archive › dc_97bc7febdf2d

La-Ribo: RNA Co-Design via Geometry-Latent Flow Matching — arXiv:2610.12236

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.12236
License (as archived): CC0-1.0
Archived: 2026-10-09T06:03:44.233Z
SHA-256 of the archived text: 48771fb32ae421745a4acb56804dfc0dfc27d22d66cc41dfed7fedbfb7b5a3e9
Stable URL of this page: https://metraipolis.com/documento/dc_97bc7febdf2d

How to cite

La-Ribo: RNA Co-Design via Geometry-Latent Flow Matching — arXiv:2610.12236 — arXiv (en), https://arxiv.org/abs/2610.12236 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_97bc7febdf2d (Metraipolis archive dc_97bc7febdf2d, sha256 48771fb32ae421745a4acb56804dfc0dfc27d22d66cc41dfed7fedbfb7b5a3e9)

BibTeX

@misc{dc97bc7febdf2d,
  title = {La-Ribo: RNA Co-Design via Geometry-Latent Flow Matching — arXiv:2610.12236},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.12236},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_97bc7febdf2d; sha256 48771fb32ae421745a4acb56804dfc0dfc27d22d66cc41dfed7fedbfb7b5a3e9},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.12236. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

RNA function arises from the coupling of nucleotide sequence and three-dimensional structure, motivating their joint design. Coordinating global folding with nucleotide-level detail remains challenging under limited structural supervision. We introduce La-Ribo, a generative framework for RNA sequence-structure co-design via geometry-latent flow matching. La-Ribo retains a sparse phosphate-sugar--base scaffold and encodes nucleotide identity and local conformation in residue-wise latents. A shared flow network generates both jointly, and an RNA-specific decoder then reconstructs all heavy atoms. To expand supervision, we construct a quality-controlled corpus of 168,561 RNA structures, integrating experimental data with predictions from three folding models, including 10,631 MSA-supported structures generated in this work. La-Ribo improves designability and codesignability over the evaluated baselines across sampling budgets and two refolding models, and the same prior supports scaffold-conditioned inverse folding without additional training.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.AI, nuovi lavori del giorno).
Categorie arXiv: Biomolecules (q-bio.BM) ; Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2610.12236 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-09T05:47:02.103Z dalla pagina https://arxiv.org/list/cs.AI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).