@inbook{fa067c22eb2a45e199532c23a72f77d4,
title = "Detection and Characterization of Ribosome-Associated Long Noncoding RNAs",
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/ ).",
keywords = "Machine learning, Ribosome profiling, Ribosome-associated, Sequence feature, lncRNA",
author = "Chao Zeng and Michiaki Hamada",
note = "Funding Information: This work was supported by the Ministry of Education, Culture, Sports, Science and Technology (KAKENHI) [grant numbers JP17K20032, JP16H05879, JP16H01318, and JP16H02484 to MH]. Publisher Copyright: {\textcopyright} 2021, Springer Science+Business Media, LLC, part of Springer Nature.",
year = "2021",
doi = "10.1007/978-1-0716-1158-6_11",
language = "English",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "179--194",
booktitle = "Methods in Molecular Biology",
}