miRNAMatcher: High throughput miRNA discovery using regular expressions obtained via a genetic algorithm

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.

Grantor dc:publisher.institution

University of the Western Cape

Year dc:date.issued

2008

Author dc:creator

• Duvenage, Eugene

Advisor dc:contributor.advisor

• Bajic, Vladimir

• miRNA
• Gene expression regulation
• Computational miRNA identification
• Hairpin structural motifs
• Secondary structure calculation
• Machine learning
• Genetic algorithm
• Regular expressions
• Genome scan
• High throughput