The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts
Open accessAbstract
It is a challenge to classify protein-coding or non-coding transcripts, especially those re-constructed from high-throughput sequencing data of poorly annotated species. This study developed and evaluated a powerful signature tool, Coding-Non-Coding Index (CNCI), by profiling adjoining nucleotide triplets to effectively distinguish protein-coding and non-coding sequences independent of known annotations. CNCI is effective for classifying incomplete transcripts and sense-antisense pairs. 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. CNCI software is available at http://www.bioinfo.org/software/cnci.
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CPC2: a fast and accurate coding potential calculator based on sequence intrinsic features
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Retracted
Metadata
- Authors
- Sun, L., Luo, H., Bu, D., Zhao, G., Yu, K., Zhang, C., Liu, Y., Chen, R., & Zhao, Y.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-07-27
- Volume
- 41
- Issue
- 17
- Pages
- e166-e166
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2061548680
- Cited by
- 2,099
- References
- 27
- FWCI
- 12.10
- Type
- journal article
- Language
- en
- Open access
- gold
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