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Updated: Jan 1, 2026

A Robust Polymerase Chain Reaction-based Assay for Quantifying Cytosine-guanine-guanine Trinucleotide Repeats in Fragile X Mental Retardation-1 Gene

A Robust Polymerase Chain Reaction-based Assay for Quantifying Cytosine-guanine-guanine Trinucleotide Repeats in Fragile X Mental Retardation-1 Gene

Published on: September 16, 2019

SMART: SuperMaximal approximate repeats tool.

Lorraine A K Ayad¹, Panagiotis Charalampopoulos^1,2, Solon P Pissis³

¹Department of Informatics, King's College London, London, UK.

Bioinformatics (Oxford, England)

|December 25, 2019

Summary

We introduce supermaximal k-mismatch repeats, a novel linear-time method for identifying repeat sequences. This approach captures all maximal repeats, offering statistically significant insights compared to current tools.

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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

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Current repeat analysis tools use maximal repeated pairs, which can be computationally intensive (quadratic time complexity).
Greedy heuristics are often employed to optimize these existing methods, potentially missing significant repeat structures.

Purpose of the Study:

To introduce a more efficient method for identifying maximal k-mismatch repeats.
To present a new class of repeats, supermaximal k-mismatch repeats, that are linear in time complexity.
To develop and evaluate a tool, SMART, for computing these novel repeats.

Main Methods:

Developed a new algorithmic approach to directly compute supermaximal k-mismatch repeats.
Implemented the algorithm in C++ to create the SMART tool.
Compared the statistical significance of supermaximal k-mismatch repeats against state-of-the-art methods.

Main Results:

Supermaximal k-mismatch repeats are linear in the input sequence length (n).
Every maximal k-mismatch repeat is a substring of a supermaximal k-mismatch repeat.
The SMART tool efficiently computes these repeats.
Supermaximal k-mismatch repeats demonstrate significantly higher statistical significance than existing methods.

Conclusions:

Supermaximal k-mismatch repeats offer a more efficient and comprehensive approach to repeat analysis.
The SMART tool provides a powerful new resource for identifying statistically significant repeat elements in biological sequences.
This work advances the field of sequence analysis by introducing a fundamentally new concept and efficient computational tool.