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Detection and Characterization of Ribosome-Associated Long Noncoding RNAs

  • Chao Zeng
  • Michiaki HamadaEmail author
Protocol
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Part of the Methods in Molecular Biology book series (MIMB, volume 2254)

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/).

Key words

lncRNA Machine learning Ribosome-associated Ribosome profiling Sequence feature 
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Notes

Acknowledgments

This work was supported by the Ministry of Education, Culture, Sports, Science and Technology (KAKENHI) [grant numbers JP17K20032, JP16H05879, JP16H01318, and JP16H02484 to MH].

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2021

Authors and Affiliations

  1. 1.AIST-Waseda University Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL)TokyoJapan
  2. 2.Faculty of Science and EngineeringWaseda UniversityTokyoJapan
  3. 3.Artificial Intelligence Research CenterNational Institute of Advanced Industrial Science and Technology (AIST)TokyoJapan
  4. 4.Institute for Medical-oriented Structural BiologyWaseda UniversityTokyoJapan
  5. 5.Graduate School of MedicineNippon Medical SchoolTokyoJapan

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