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README.md ADDED
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+ ---
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+ language: rna
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+ tags:
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+ - Biology
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+ - RNA
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+ license:
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+ - agpl-3.0
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+ size_categories:
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+ - 1K<n<10K
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+ source_datasets:
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+ - multimolecule/rfam
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+ task_categories:
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+ - text-generation
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+ - fill-mask
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+ task_ids:
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+ - language-modeling
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+ - masked-language-modeling
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+ pretty_name: bpRNA-new
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+ library_name: multimolecule
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+ ---
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+
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+ # bpRNA-new
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+
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+ bpRNA-new is a database of single molecule secondary structures annotated using bpRNA.
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+
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+ bpRNA-new is a dataset of RNA families from Rfam 14.2, designed for cross-family validation to assess generalization capability.
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+ It focuses on families distinct from those in [bpRNA-1m](../bprna), providing a robust benchmark for evaluating model performance on unseen RNA families.
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+
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+ ## Disclaimer
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+
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+ This is an UNOFFICIAL release of the bpRNA-new by Kengo Sato, et al.
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+
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+ **The team releasing bpRNA-new did not write this dataset card for this dataset so this dataset card has been written by the MultiMolecule team.**
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+
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+ ## Dataset Description
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+
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+ - **Homepage**: https://multimolecule.danling.org/datasets/bprna-new
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+ - **datasets**: https://huggingface.co/datasets/multimolecule/bprna-new
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+ - **Point of Contact**: [Kengo Sato](mailto:satoken@bio.keio.ac.jp)
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+
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+ ## Related Datasets
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+
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+ - [bpRNA-1m](https://huggingface.co/datasets/multimolecule/bprna): A database of single molecule secondary structures annotated using bpRNA.
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+ - [bpRNA-spot](https://huggingface.co/datasets/multimolecule/bprna-spot): A subset of bpRNA-1m that applies [CD-HIT (CD-HIT-EST)](https://sites.google.com/view/cd-hit) to remove sequences with more than 80% sequence similarity from bpRNA-1m.
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+ - [ArchiveII](https://huggingface.co/datasets/multimolecule/archiveii): A database of RNA secondary with the same families as RNAStrAlign, usually used for testing.
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+
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+ ## License
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+
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+ This dataset is licensed under the [AGPL-3.0 License](https://www.gnu.org/licenses/agpl-3.0.html).
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+
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+ ```spdx
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+ SPDX-License-Identifier: AGPL-3.0-or-later
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+ ```
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @article{sato2021rna,
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+ author = {Sato, Kengo and Akiyama, Manato and Sakakibara, Yasubumi},
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+ journal = {Nature Communications},
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+ month = feb,
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+ number = 1,
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+ pages = {941},
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+ publisher = {Springer Science and Business Media LLC},
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+ title = {{RNA} secondary structure prediction using deep learning with thermodynamic integration},
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+ volume = 12,
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+ year = 2021
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+ }
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+ ```
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