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How does the coding non coding index ( cnci ) work?


Asked by Lexie Hebert on Dec 01, 2021 FAQ



The implementation of CNCI offered highly accurate classification of transcripts assembled from whole-transcriptome sequencing data in a cross-species manner, that demonstrated gene evolutionary divergence between vertebrates, and invertebrates, or between plants, and provided a long non-coding RNA catalog of orangutan.
Keeping this in consideration,
CNCI analysis is a method to distinguish non-coding from coding transcripts by the traits of adjacent nucleotide triplets. It does not depend on known annotation files and can effectively predict incomplete transcripts and antisense transcripts, and transcript is noncoding RNA when score < 0.
Consequently, Because CNIT, similar to CNCI, classifies protein-coding and non-coding RNAs solely based on intrinsic sequence composition, it is potentially applicable to a variety of species lacking a whole-genome sequence or with poorly annotated information.
Moreover,
Numerous studies show that non-coding RNAs (ncRNAs) have critical roles in diverse biological processes from plants to animals ( 1–4 ), such as sponging by microRNAs ( 5 ), cell development ( 6 ), acting as modular scaffolds ( 7) and regulating epigenetic inheritance ( 8 ).
Furthermore,
The data of six species were identified by the five software programs: CNIT, CNCI, CPC2, CPAT (It only can identify four species) ( 17) and PLEK ( 18) software, and the accuracy was calculated (Figure 1B ). Compared with CNCI, CNIT has higher accuracy.