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New REFLEX method generates diverse RNA ensembles with high fidelity

Researchers have developed REFLEX, a new method for generating RNA ensembles that accurately captures diverse conformational states without collapsing to averaged structures or drifting into unsupported regions. This sequence-conditioned generator utilizes a heteroscedastic stochastic bridge on SE(3), calibrated by experimental B-factors during training to adjust local perturbation scales. At inference, REFLEX relies solely on the input sequence, demonstrating superior precision-recall trade-offs for ensemble coverage on a multi-conformer RNA benchmark. AI

IMPACT This method could advance computational biology and drug discovery by improving the modeling of RNA structures and functions.

RANK_REASON The item is a research paper detailing a new method for RNA ensemble generation, published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New REFLEX method generates diverse RNA ensembles with high fidelity

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The item is a research paper detailing a new method for RNA ensemble generation, published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Wanli Ma, Tianmeng Hu, Ke Li ·

    REFLEX: RNA Ensemble Generation via Flexibility-Calibrated Stochastic Bridge

    arXiv:2610.26261v3 Announce Type: replace Abstract: RNA molecules often function through multiple experimentally observed conformational states. A central challenge is to capture ensemble diversity without sacrificing structural fidelity: samples may collapse toward averaged repr…