title: Computational Analysis of LncRNA from cDNA Sequences.
abstract: Based on recent findings, long noncoding (lnc) RNAs represent a potential class of functional molecules within the cell. In this chapter we describe a computational scheme to identify and classify lncRNAs within maize from full-length cDNA sequences to designate subsets of lncRNAs for which biogenesis and regulatory mechanisms may be verified at the bench. We make use of the Coding Potential Calculator and specific Python scripts in our approach.
authors.affiliation: Department of Biological Science, Florida State University, 319 Stadium Drive, Tallahassee, FL, 32306-4295, USA.
authors.forename: Susan
authors.initials: S
authors.lastname: Boerner
authors.affiliation: Department of Biological Science, Florida State University, 319 Stadium Drive, Tallahassee, FL, 32306-4295, USA. mcginnis@bio.fsu.edu.
authors.forename: Karen M
authors.initials: KM
authors.lastname: McGinnis
mesh_terms: D018076:DNA, Complementary / Q000235:genetics*; D018745:Genome, Plant; D023281:Genomics / Q000379:methods*; D006801:Humans; D062085:RNA, Long Noncoding / Q000235:genetics*; D018749:RNA, Plant / Q000235:genetics*; D012984:Software; D003313:Zea mays / Q000235:genetics*
chemical_list: D018076:DNA, Complementary; D062085:RNA, Long Noncoding; D018749:RNA, Plant
keywords: Long noncoding RNA; Maize; NATs; miRNA; siRNA