Microarray gene expression data analysis using machine learning and neural networks

<p>"As an important experimental technology, DNA microarray provides an effective way to measure the expression levels of tens of thousands of genes simultaneously under different conditions, which makes it possible to investigate the gene activities of the whole genome. However, computational challenges have to be faced as a result of the large volume of generated data. In this dissertation, two important applications of microarray data, i.e., genetic regulatory networks inference and cancer classification, are addressed with machine learning and neural networks"--Abstract, page iii.</p>

Name thesis:degree_name

Ph. D. in Electrical Engineering

Grantor

University of Missouri--Rolla

Year dc:date.available

2016

Author dc:creator

• Xu, Rui

• Electrical and Computer Engineering

Repository record dc:identifier

https://scholarsmine.mst.edu/doctoral_dissertations/1696

OAI identifier oai:identifier

oai:scholarsmine.mst.edu:doctoral_dissertations-2698