Deep-learning-based approach for identification of eukaryotic sequences in the metagenomic data.
copied from cf-staging / tiaraDeep-learning-based approach for identification of eukaryotic sequences in the metagenomic data powered by PyTorch. The sequences are classified in two stages: In the first stage, the sequences are classified to classes: archaea, bacteria, prokarya, eukarya, organelle and unknown. In the second stage, the sequences labeled as organelle in the first stage are classified to either mitochondria, plastid or unknown. For more information, please refer to our paper: Tiara: Deep learning-based classification system for eukaryotic sequences. (DOI: https://doi.org/10.1093/bioinformatics/btab672)
