Recent transcriptome studies have revealed that 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. 10-fold cross-validation on the training dataset and independent testing on three large standalone 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.

The coding potential calculator tool reads FASTA data format as input. "A sequence in FASTA format begins with a single-line description, followed by lines of sequence data. The description line is distinguished from the sequence data by a greater-than (">") symbol in the first column.(ncbi) "

If you still do not very clear with what we are talking about, please refer to lemma FASTA at CPC Glossary.

To start your calculate task, click HERE. And there is a step by setp guide to teach users how to use our CPC online. After user input sequences and run, the calculator will assign user a Task ID which is unique. You can use it to access your results at our Data Retrival Page.