Detection and Characterization of Ribosome-Associated Long Noncoding RNAs

Chao Zeng, Michiaki Hamada

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Ribosome profiling shows potential for studying the function of long noncoding RNAs (lncRNAs). We introduce a bioinformatics pipeline for detecting ribosome-associated lncRNAs (ribo-lncRNAs) from ribosome profiling data. Further, we describe a machine-learning approach for the characterization of ribo-lncRNAs based on their sequence features. Scripts for ribo-lncRNA analysis can be accessed at (https://ribolnc.hamadalab.com/ ).

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages179-194
Number of pages16
DOIs
Publication statusPublished - 2021

Publication series

NameMethods in Molecular Biology
Volume2254
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Machine learning
  • Ribosome profiling
  • Ribosome-associated
  • Sequence feature
  • lncRNA

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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