Functional annotation of enzyme-encoding genes using deep learning with transformer layers

Supplementary datasets for the paper "Improved annotation of enzyme-encoding genes using deep learning with transformer layers". The datasets include Supplementary Data 1 (Predicted EC numbers for protein sequences from Swiss-Prot database using DeepECtransformer), Supplementary Data 2 (Visualization of the latent representations of enzyme sequences in the Swiss-Prot database using TMAP), Supplementary Data 3 (Commonly highlighted motifs for each EC number using DeepEC v2 neural network), Supplementary Data 4 (Sequences for each of strain specific alleles), Supplementary Data 5 (EC number prediction results for the y-ome proteins), Supplementary Data 6 (EC numbers of 128,100,490 protein sequences in 70,600 genomes in NCBI), and Supplementary Data 7 (Solubility prediction results for 295 y-ome proteins).本数据集为论文《基于Transformer层深度学习的酶编码基因注释优化》的补充数据集。该数据集包含补充数据1（基于DeepECtransformer对Swiss-Prot数据库中蛋白质序列预测得到的EC（Enzyme Commission）编号）、补充数据2（使用TMAP对Swiss-Prot数据库中酶序列的潜在表征进行可视化的结果）、补充数据3（基于DeepEC v2神经网络针对各EC编号提取的高频特征基序）、补充数据4（各菌株特异性等位基因对应的蛋白质序列）、补充数据5（y-ome蛋白质的EC编号预测结果）、补充数据6（NCBI数据库70600个基因组中128100490条蛋白质序列对应的EC编号）以及补充数据7（295个y-ome蛋白质的可溶性预测结果）。