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

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Authors: Bin Ye, Junfeng Xia, Xia Wan, Min Wu, Satoshi Chiba
Cited by: 0

Abstract

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.

Fields of Study & Subjects

Environmental DNA in Biodiversity Studies Invertebrate Taxonomy and Ecology Genomics and Phylogenetic Studies

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 January 2026