miRNAMatcher: High throughput miRNA discovery using regular expressions obtained via a genetic algorithm
type: CreativeWork
description: In summary there currently exist techniques to discover miRNA however both require many calculations to be performed during the identification limiting their use at a genomic level. Machine learning techniques are currently providing the best results by combining a number of calculated and statistically derived features to identify miRNA candidates, however almost all of these still include computationally intensive secondary-structure calculations. It is the aim of this project to produce a miRNA identification process that minimises and simplifies the number of computational elements required during the identification process.
abstract: In summary there currently exist techniques to discover miRNA however both require many calculations to be performed during the identification limiting their use at a genomic level. Machine learning techniques are currently providing the best results by combining a number of calculated and statistically derived features to identify miRNA candidates, however almost all of these still include computationally intensive secondary-structure calculations. It is the aim of this project to produce a miRNA identification process that minimises and simplifies the number of computational elements required during the identification process.
author: Duvenage, Eugene
keywords: miRNA, Gene expression regulation, Computational miRNA identification, Hairpin structural motifs, Secondary structure calculation, Machine learning, Genetic algorithm, Regular expressions, Genome scan, High throughput
date published: 2008
date modified: 2026-07-24T06:00:38Z
provider: University of the Western Cape
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of the Western Cape