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Updated: Mar 21, 2026
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Identification of Circular RNAs using RNA Sequencing
Published on: November 14, 2019
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Circular sequence comparison: algorithms and applications
Roberto Grossi1, Costas S Iliopoulos2, Robert Mercas3
1Department of Informatics, University of Pisa, Pisa, Italy ; ERABLE team, INRA, Paris, France.
Algorithms for Molecular Biology : AMB
|May 12, 2016
Summary
This study introduces a novel q-gram based distance measure for efficient circular sequence comparison. The new method significantly outperforms traditional techniques in speed while maintaining high accuracy for DNA, RNA, and protein sequences.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Sequence comparison is crucial for bioinformatics tasks like phylogenetic reconstruction and genome assembly.
- Traditional methods rely on sequence alignment, which is computationally expensive for circular sequences (super-quadratic to cubic time).
Purpose of the Study:
- To introduce a new, efficient distance measure for circular sequence comparison.
- To demonstrate the effectiveness and computational advantages of the proposed method.
Main Methods:
- Development of a novel distance measure based on q-grams.
- Application and evaluation of the q-gram based measure for circular sequence comparison.
Main Results:
- The q-gram based approach offers orders-of-magnitude improvement in efficiency compared to traditional methods.
- The method maintains competitive accuracy with state-of-the-art techniques.
- Experimental validation on real DNA, RNA, protein, and synthetic sequences.
Conclusions:
- The proposed q-gram based distance measure provides a computationally efficient and accurate solution for circular sequence comparison.
- This advancement has significant implications for various bioinformatics applications involving circular molecules.
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