The CNIT sever accepts RNA transcript sequences as input, and outputs assessed protein-coding potential of the transcripts. Powered by a novel model based on sequence intrinsic features, the updated CNIT runs faster than the previous CNCI, with an improved accuracy and more species, especially for plant sequence prediction. Please feel free to reach us by guojincheng@ict.ac.cn for any questions and comments. Also try the NONCODE for an integrative annotation of your lncRNAs.
Related databases:
Citations:
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1. Guo, J. C. Zhao, Y. et al. CNIT: a fast and accurate web tool for identifying protein-coding and long non-coding transcripts based on intrinsic sequence composition. Nucleic acids research 47, W516-W522, doi:10.1093/nar/gkz400 (2019).
2. Sun, L. Zhao, Y. et al. Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts. Nucleic acids research 41, e166, doi:10.1093/nar/gkt646 (2013).
