Multi‐barcoding‐based Gastropoda identification using hierarchical attention network with staged curriculum learning

This dataset contains multiple types of DNA barcoding sequences of COI, 16S, H3, 18S, ITS1, and ITS2 of Gastropoda species accessed from GenBank and BOLD, and the corresponding the RNA secondary structure embedding of the 6 barcoding types and the DNA barcoding embedding of COI sequences. The RNA secondary structure embeddings are extracted using the RNA foundation model ERNIE-RNA (https://github.com/Bruce-ywj/ERNIE-RNA) (Yin et al. 2025, Nature Communications, 16: 10076). The DNA barcoding embedding of COI sequences is extracted using the DNA barcoding foundation model BarcodeMAE (https://github.com/bioscan-ml/BarcodeMAE) (Safari et al. 2025, arXiv, 2502.18405). These sequences and embeddings are used for training, validation, testing, and independent testing data for a deep learning model named SnailBaLLsp, which is developed for multi‐barcoding‐based Gastropoda identification using hierarchical attention network with staged curriculum learning.
, , # Multi‐barcoding‐based Gastropoda identification using hierarchical attention network with staged curriculum learning

Dataset DOI: [10.5061/dryad.ttdz08m9c](10.5061/dryad.ttdz08m9c)

## Description of the data and file structure

Datasets for training, validation, testing, and independent testing contain several columns representing the information for sequence source, length, and hierarchical taxonomy names in several taxonomy level. The COI data has the full records of all taxonomy levels. The other five types of barcoding data have partial samples consistent with the COI data, which have the index corresponding to sample index of COI samples.

The embedding data are extracted by ERNIE-RNA (Yin et al. 2025, Nature Communications, 16: 10076) (for all the six barcoding types) and BarcodeMAE (Safari et al. 2025, arXiv, 2502.18405) (only for COI barcoding), respectively. The protocol of embedding extraction could be found in the manual of ERNIE-RNA ([https://github.com/Bruce-ywj/ERNIE-R...,