Workflow development for the functional characterization of ncRNAs

  • Markus Wolfien*
  • , David Leon Brauer
  • , Andrea Bagnacani
  • , Olaf Wolkenhauer
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

17 Scopus citations

Abstract

During the last decade, ncRNAs have been investigated intensively and revealed their regulatory role in various biological processes. Worldwide research efforts have identified numerous ncRNAs and multiple RNA subtypes, which are attributed to diverse functionalities known to interact with different functional layers, from DNA and RNA to proteins. This makes the prediction of functions for newly identified ncRNAs challenging. Current bioinformatics and systems biology approaches show promising results to facilitate an identification of these diverse ncRNA functionalities. Here, we review (a) current experimental protocols, i.e., for Next Generation Sequencing, for a successful identification of ncRNAs; (b) sequencing data analysis workflows as well as available computational environments; and (c) state-of-the-art approaches to functionally characterize ncRNAs, e.g., by means of transcriptome-wide association studies, molecular network analyses, or artificial intelligence guided prediction. In addition, we present a strategy to cover the identification and functional characterization of unknown transcripts by using connective workflows.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages111-132
Number of pages22
DOIs
StatePublished - 2019
Externally publishedYes

Publication series

NameMethods in Molecular Biology
Volume1912
ISSN (Print)1064-3745

Keywords

  • Co-expression analysis
  • Data analysis
  • Experimental RNA discovery
  • Machine learning
  • Network analysis
  • Next Generation Sequencing
  • Transcript identification
  • Workflow
  • ncRNA

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