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README: Zenodo DOI badge #44

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DylanYang merged 1 commit into from
Nov 12, 2026
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README: Zenodo DOI badge #44

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<a href="LICENSE"><img src="https://img.shields.io/badge/License-Apache_2.0-blue.svg" alt="License: Apache 2.0" /></a>
<img src="https://img.shields.io/badge/python-%3E%3D3.10-blue.svg" alt="Python >= 3.10" />
<a href="#installation"><img src="https://img.shields.io/badge/install-conda-44A833.svg" alt="Install with conda" /></a>
<a href="https://doi.org/10.5281/zenodo.24148643"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.24148643.svg" alt="DOI" /></a>
</p>

RFoldSearch enables fast RNA tertiary-structure search with 3Dr, a learned discrete structural alphabet. Each nucleotide is described by a 17-D vector: the rigid-body transform to its nearest non-sequential spatial neighbour and its local context. A VQ-VAE quantises this vector into one of 80 states, converting RNA chains into token strings. Targets sharing at least two token k-mers on a common diagonal with the query pass the prefilter, and the top N are aligned by affine-gap token Smith-Waterman, which gives the alignment score and the nucleotide correspondence. For the default search mode, RFoldSearch estimates token-alignment E-values using a database-specific Gumbel model followed by calibration of unrelated background counts. Hits are ranked by a structure score that combines the token-alignment score with the structural similarity of the aligned nucleotides, independently of the reported E-value. RFoldSearch-TM instead ranks candidates by US-align TM-score and does not report token-alignment E-values.
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