(Datasets) Systematic representation and optimization enable the inverse design of cross-species regulatory sequences in bacteria

This repository supplies the essential datasets for pretraining and fine-tuning as involved in the research paper. ”bacteria_all_no_unknown2kspe_180spe_norepeat_classlabel_train995.txt“ represents the "pretrain_seqs.txt" in `aae_meta.py`, while "BS_EC_PA_JY_train_comparative_genome_paper_storzdRNAseq.txt"represents the finetune_file, implemented in `aae_genus.py` and `aae_meta.py`. All other dataset for evaluation, including supervised training data are directly uploaded to github repository (https://github.com/WangLabTHU/DeepCROSS/tree/main).