CoRAL: predicting non-coding RNAs from small RNA-sequencing data
CoRAL: predicting non-coding RNAs from small RNA-sequencing data is a scholarly work by Lyle H. Ungar, Paul Ryvkin, and Yuk Yee Leung, published in 2013 in ''Nucleic Acids Research''. The main subjects of the publication include methylation, genome, genetics, intergenic region, gene, small nucleolar RNA, non-coding RNA, small RNA, computational biology, long non-coding RNA, human genome, high-coverage sequencing, microRNA, RNA splicing, ribonucleic acid, and biology. The authors evaluated CoRAL using genome-wide small RNA sequencing data sets from four human tissue types and were able to classify six different types of RNAs with ∼80% cross-validation accuracy.