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.

本数据集包含从GenBank与BOLD数据库获取的腹足纲（Gastropoda）物种的多类DNA条形码序列，涵盖COI、16S、H3、18S、ITS1及ITS2共6类标记基因；同时附带上述6类条形码的RNA二级结构嵌入向量，以及COI序列的DNA条形码嵌入向量。其中，RNA二级结构嵌入向量通过RNA基础模型ERNIE-RNA（https://github.com/Bruce-ywj/ERNIE-RNA）提取（Yin 等，2025，《自然·通讯》，16:10076）；COI序列的DNA条形码嵌入向量则通过DNA条形码基础模型BarcodeMAE（https://github.com/bioscan-ml/BarcodeMAE）提取（Safari 等，2025，arXiv，2502.18405）。上述序列与嵌入向量将作为训练、验证、测试及独立测试数据集，用于一款名为SnailBaLLsp的深度学习模型。该模型基于分阶段课程学习的层级注意力网络开发，旨在依托多条形码数据实现腹足纲物种的精准鉴定。