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Related Experiment Video

Updated: May 24, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

To detect and analyze sequence repeats whatever be their origin.

Jacques Nicolas¹

¹IRISA, INRIA centre de recherche Rennes-Bretagne Atlantique, Campus Universitaire de Beaulieu, Rennes Cedex, France. jnicolas@irisa.fr

Methods in Molecular Biology (Clifton, N.J.)

|February 28, 2012

Summary

This study reviews foundational concepts for identifying mobile genetic elements. It highlights efficient algorithms and data structures for genomic repeat analysis and discusses knowledge management for mobile element research.

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Numerous software programs exist for identifying mobile genetic elements, but shared foundational concepts are often overlooked.
The increasing volume of sequence data necessitates efficient algorithms and data structures for genomic analysis.
Growing knowledge of mobile element architecture requires better tools for managing and comparing research findings.

Purpose of the Study:

To review fundamental concepts in mobile genetic element identification.
To discuss efficient algorithms and data structures for handling large genomic datasets.
To explore knowledge management strategies for mobile element research.

Main Methods:

Review of existing literature and software for mobile genetic element identification.
Discussion of string indexing and string matching algorithms for sequence analysis.
Exploration of data and knowledge management techniques relevant to genomic research.

Main Results:

Key concepts underlying genomic repeat searches are identified.
An overview of efficient string indexing and matching techniques is provided.
Considerations for future knowledge management tools in mobile element research are presented.

Conclusions:

Standardizing foundational concepts can streamline software development for mobile element identification.
Efficient algorithms and data structures are crucial for managing the deluge of genomic sequence data.
Improved knowledge management tools are needed to support the growing body of research on mobile elements.