ArticleNucleic acids research2007
CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine.
Article in Nucleic acids research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,556 papers.
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1,556 citing papers in PubMed.
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- Elucidation of sugar metabolic profiles and transcriptional regulatory networks during the developmental stages of sweet corn kernels.iScience · 2026Article
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- Transcriptomic analysis of genes in bladder cancer patients with resistance to neoadjuvant chemoimmunotherapy.BMC cancer · 2026Article
- Identification of candidate genes and ceRNA networks of HPG axis in regulating sexual precocity of roosters by whole transcriptomic sequencing.BMC genomics · 2026Article
1,496 more citing papers are in PubMed but not listed here.
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7 authors.
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Abstract
Recent transcriptome studies have revealed that a large number of transcripts in mammals and other organisms do not encode proteins but function as noncoding RNAs (ncRNAs) instead. As millions of transcripts are generated by large-scale cDNA and EST sequencing projects every year, there is a need for automatic methods to distinguish protein-coding RNAs from noncoding RNAs accurately and quickly. We developed a support vector machine-based classifier, named Coding Potential Calculator (CPC), to assess the protein-coding potential of a transcript based on six biologically meaningful sequence features. Tenfold cross-validation on the training dataset and further testing on several large datasets showed that CPC can discriminate coding from noncoding transcripts with high accuracy. Furthermore, CPC also runs an order-of-magnitude faster than a previous state-of-the-art tool and has higher accuracy. We developed a user-friendly web-based interface of CPC at http://cpc.cbi.pku.edu.cn. In addition to predicting the coding potential of the input transcripts, the CPC web server also graphically displays detailed sequence features and additional annotations of the transcript that may facilitate users' further investigation.
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