Here's a breakdown of the data we used to train eFold. You can find these datasets on Hugging Face. The raw data in on this google drive.
| Training stage | Name on HuggingFace | Source | Method | Number of sequences | Families | length [10, 199] | length [200, 499] | length [500, 999] | length [1000, 1999] | length [2000, inf] |
|---|---|---|---|---|---|---|---|---|---|---|
| Pre-training | rnacentral_synthetic | Sequences from RNA central | RNAstructure | 226'729 | All known families | 176'486 | 49'463 | 780 | 0 | 0 |
| Pre-training | ribo500-blast | Ribonanza Competition | RNAstructure + DMS and/or SHAPE | 46'060 | Unlabelled | 46'049 | 11 | 0 | 0 | 0 |
| Pre-training | bpRNA-1m | bpRNA-1m | Covariance analysis | 66'715 | Unlabelled, sRNA, tRNA | 48'090 | 6'167 | 2'829 | 9'260 | 369 |
| Fine-tuning | pri_miRNA | This work | RNAstructure + DMS | 1'098 | pri-miRNA | 0 | 1'098 | 0 | 0 | 0 |
| Fine-tuning | human_mRNA | This work | RNAstructure + DMS | 1'456 | mRNA | 0 | 493 | 882 | 81 | 0 |
| Testing | PDB | PDB | NMR, crystallography | 355 | Short non-coding RNA | 343 | 6 | 6 | 0 | 0 |
| Testing | viral_fragments | Peer-reviewed literature | RNAstructure + DMS | 40 | Viral RNA | 12 | 17 | 11 | 0 | 0 |
| Testing | lncRNA | Bugnon and al, 2022 | RNAstructure + DMS | 30 | Long non-coding RNA | 0 | 2 | 1 | 27 | 0 |
| Testing | archiveII | Archive II | Covariance analysis | 3'370 | rRNA, tRNA, tmRNA, unlabelled | 2'004 | 1'276 | 79 | 11 | 0 |
The normalisation, filtering and replicates matching of SEISMIC data is made using seismic__postprocessing.py.
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