Publication Date
2009
Degree Type
Master's Project
Degree Name
Master of Science (MS)
Department
Computer Science
Abstract
MicroRNAs are a type of non-coding RNA that were discovered less than a decade ago but are now known to be incredibly important in regulating gene expression despite their small size. However, due to their small size, and several other limiting factors, experimental procedures have had limited success in discovering new microRNAs. Computational methods are therefore vital to discovering novel microRNAs. Many different approaches have been used to scan genomic sequences for novel microRNAs with varying degrees of success. This work provides an overview of these computational methods, focusing particularly on those methods based on machine learning techniques. The results of experiments performed on several of the machine learning based microRNA detectors are provided along with an analysis of their performance.
Recommended Citation
Ikeoka, Steve, "Analysis of Machine Learning Based Methods for Identifying MicroRNA Precursors" (2009). Master's Projects. 55.
DOI: https://doi.org/10.31979/etd.hvfw-ew3m
https://scholarworks.sjsu.edu/etd_projects/55
