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Related Experiment Video

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Workflow Development for the Functional Characterization of ncRNAs.

Markus Wolfien1, David Leon Brauer2, Andrea Bagnacani2

  • 1Department of Systems Biology and Bioinformatics, Institute of Computer Science, University of Rostock, Rostock, Germany. markus.wolfien@uni-rostock.de.

Methods in Molecular Biology (Clifton, N.J.)
|January 13, 2019
PubMed
Summary
This summary is machine-generated.

Non-coding RNAs (ncRNAs) play regulatory roles, but their diverse functions are hard to predict. This review covers ncRNA identification, analysis, and functional characterization methods.

Keywords:
Co-expression analysisData analysisExperimental RNA discoveryMachine learningNetwork analysisNext Generation SequencingTranscript identificationWorkflowncRNA

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Non-coding RNAs (ncRNAs) are increasingly recognized for their regulatory roles in diverse biological processes.
  • Numerous ncRNA subtypes have been identified, exhibiting complex interactions with DNA, RNA, and proteins, making functional prediction challenging.
  • Advancements in bioinformatics and systems biology offer promising avenues for identifying ncRNA functionalities.

Purpose of the Study:

  • To review current experimental protocols for ncRNA identification, including Next Generation Sequencing (NGS).
  • To discuss sequencing data analysis workflows and computational environments for ncRNA research.
  • To present state-of-the-art computational approaches for functional characterization of ncRNAs.

Main Methods:

  • Review of experimental protocols for ncRNA identification (e.g., NGS).
  • Analysis of bioinformatics workflows and computational environments for sequencing data.
  • Exploration of functional characterization methods like transcriptome-wide association studies, network analysis, and AI-guided prediction.

Main Results:

  • Comprehensive overview of established and emerging techniques for ncRNA identification and functional analysis.
  • Integration of experimental and computational strategies for a holistic approach.
  • Presentation of a novel strategy for identifying and characterizing unknown transcripts using connective workflows.

Conclusions:

  • Effective identification and functional characterization of ncRNAs require integrated experimental and computational approaches.
  • Bioinformatics and systems biology are crucial for deciphering the complex roles of ncRNAs.
  • The proposed strategy offers a pathway for exploring the functional landscape of previously uncharacterized transcripts.