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Updated: May 30, 2026
09:05
Pooled CRISPR-Based Genetic Screens in Mammalian Cells
Published on: September 4, 2019
From structure prediction to genomic screens for novel non-coding RNAs
1Center for non-coding RNA in Technology and Health, IBHV University of Copenhagen, Frederiksberg, Denmark. gorodkin@rth.dk
Plos Computational Biology
|August 11, 2011
Summary
Discovering novel non-coding RNA genes relies on computational methods that analyze RNA structure. These structure-based genomic screens identify regulatory RNA elements in genomes and mRNAs.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Non-coding RNAs (ncRNAs) are abundant and play crucial regulatory roles.
- RNA structure is fundamental to its function, with many ncRNAs being highly structured.
- Genomic data and structure prediction enable large-scale ncRNA discovery.
Purpose of the Study:
- To review computational methods for identifying novel ncRNA genes and regulatory RNA structures.
- To explain the principles of RNA folding and structure-based genomic screening.
- To discuss the strengths and weaknesses of different computational strategies.
Main Methods:
- RNA folding and structure prediction algorithms.
- Comparative analysis of structure-preserving base pair changes.
- Genomic screens utilizing RNA structure as a primary feature.
Main Results:
- Computational screens can identify ncRNAs based on their structural characteristics.
- Structure-based methods, particularly comparative analysis, improve accuracy in ncRNA detection.
- Novel ncRNA genes and regulatory RNA structures can be discovered de novo.
Conclusions:
- RNA structure is a powerful feature for discovering novel ncRNAs and regulatory elements.
- Structure-based comparative analysis is a key component of modern genomic screens.
- Different computational strategies offer complementary approaches for ncRNA research.
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