RNAJog: an autoregressive generative model for codon optimization

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STEP 1: Choose a model version and input sequence RNAJog RNAJog-Zero RNAJog: Trained on iCodon mRNA data set  (Example) Protein sequence RNA sequence RNAJog-Zero: Trained on random generated mRNA sequences  (Example) Protein sequence RNA sequence

STEP 2: Optional parameters (1) MFE-CAI weight       (2) Subsequences that need to be excluded (e.g., restriction enzyme sites, separated by ”;”). (3) Select Expression Host Homo sapiens Escherichia coli User defined (4) Decoding strategy Greedy Sample

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If you use RNAJog, please cite the following paper:
Jiaqi Huang et al. Fast Multi-objective RNA Optimization with Autoregressive Reinforcement Learning. In submisson.