Computational analysis of noncoding RNAs

• Main Authors: Washietl, Stefan (Contributor), Will, Sebastian (Contributor), Hendrix, David A. (Contributor), Goff, Loyal (Contributor), Rinn, John L. (Author), Berger, Bonnie (Contributor), Kellis, Manolis (Contributor)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Department of Mathematics (Contributor)
• Format: Article
• Language: English
• Published: John Wiley & Sons, Inc, 2014-05-21T18:32:50Z.
• Subjects: Article
• Online Access: Get fulltext

 Noncoding RNAs have emerged as important key players in the cell. Understanding their surprisingly diverse range of functions is challenging for experimental and computational biology. Here, we review computational methods to analyze noncoding RNAs. The topics covered include basic and advanced techniques to predict RNA structures, annotation of noncoding RNAs in genomic data, mining RNA-seq data for novel transcripts and prediction of transcript structures, computational aspects of microRNAs, and database resources.