jiahaozhang2003/beacon-degradation

BEACON — Degradation

RNA degradation / chemical-probing measurements with sequence and structure annotations.

Official data from the shared BEACON/RNABenchmark Drive folder: https://drive.google.com/drive/folders/19ddrwI8ycvIxkgSV3gDo_VunLofYd4-6?hl=en.

This repository is the standardized Hugging Face publication of the official task data. The data/ directory is the canonical viewer-friendly layer, and the original files and directory layout are preserved for reproducibility. beacon_manifest.json records source file IDs, checksums, sizes, split counts, schema, and processing notes. Interrupted-upload artifacts ending in .partial are retained only in the GPUHub raw staging area and excluded from the published repository.

Canonical splits

Split	Rows	File
train	2155	data/train.parquet
validation	245	data/validation.parquet
test	3634	data/test.parquet

Standardized schema

Field	Arrow type
index	int64
id	string
sequence	string
structure	string
predicted_loop_type	string
signal_to_noise	double
SN_filter	int64
seq_length	int64
seq_scored	int64
reactivity_error	list<element: double>
deg_error_Mg_pH10	list<element: double>
deg_error_pH10	list<element: double>
deg_error_Mg_50C	list<element: double>
deg_error_50C	list<element: double>
reactivity	list<element: double>
deg_Mg_pH10	list<element: double>
deg_pH10	list<element: double>
deg_Mg_50C	list<element: double>
deg_50C	list<element: double>
reactivity_min	double
deg_Mg_pH10_min	double
deg_pH10_min	double
deg_Mg_50C_min	double
deg_50C_min	double
train_tensor	list<element: list<element: double>>

Standardization notes

• Canonical split names are train, validation, and test; source val.csv/val_1.json is published as validation.
• The official raw directory tree is preserved alongside the standardized data/*.parquet files.
• Source file names and target paths are retained in beacon_manifest.json for provenance.
• The keyed JSON records are row-normalized into one Parquet row per sample; nested per-nucleotide arrays are preserved.

Usage

from datasets import load_dataset

dataset = load_dataset("jiahaozhang2003/beacon-degradation")

Reproducibility

This repository was generated on GPUHub from the public Drive source with the RiboLoop downstream benchmark data-staging script. No model outputs or training artifacts are included.