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

Source data and Supplementary datasets for the paper "Functional annotation of enzyme encoding genes using deep learning with transformer layers". The datasets include uniprot dataset, Supplementary Data 1 (Predicted EC numbers for amino acid 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 amino acid sequences in 70,600 genomes in NCBI), and Supplementary Data 7 (Solubility prediction results for 295 y-ome proteins).