Diverse database and machine learning model to narrow the generalization gap in RNA structure prediction

This dataset contains RNA secondary structure data used for training and testing eFold, a deep learning model for RNA secondary structure prediction. The dataset comprises three main components: (1) experimentally determined secondary structure models for 1,098 pri-miRNAs and 1,456 human mRNA regions derived from DMS-MaP-seq chemical probing experiments, representing the original contribution of this work; (2) a curated pre-training dataset combining subsets of bpRNA (base-pair RNA database) and RNAstralign databases, filtered to remove redundant sequences and ArchiveII sequences as described in the associated publication; and (3) benchmark test sets for evaluating model performance on long and diverse RNA structures.
The dataset includes sequence files in FASTA format and corresponding secondary structure annotations in dot-bracket notation. Structure models represent experimentally validated folding patterns with reactivity data from chemical probing assays. The pri-miRNA structures r..., , # Diverse database and machine learning model to narrow the generalization gap in RNA structure prediction

Dataset DOI: [10.5061/dryad.79cnp5j95](https://doi.org/10.5061/dryad.79cnp5j95)

## Description of the data and file structure

The data is a json file, structured as follows:

```
sequence_name:
sequence: AAGUGAAG.. # string of nucleotides
structure: [[171, 317], [351, 403], ...] # list of base pairs
shape: [0.4519, 1.0903, 0.5035, 0.1382,...] # list of normalized shape reactivities (when available)
dms: [1.0, 0.7283, -1000.0, -1000.0, ...] # list of normalized DMS reactivities (when available). Since DMS only reacts to A and C, all reactivities for G and U are set to -1000.
```

### Files and variables

#### File: pri_miRNA.json

**Description:** Original contribution. See section Methods of [https://www.biorxiv.org/content/10.1101/2024.01.24.577093v4](https://www.biorxiv.org/content/10.1101/2024.01.24.577093v4).

#### File: human_mRNA.json

**Description:** Orig...,