Classification of Cancer using Epigenetic Markers in the Head and Neck

dc.contributor.author	Muhammad Omar Zeb, Supervised by Dr Hasan Sajid
dc.date.accessioned	2021-06-16T09:24:10Z
dc.date.available	2021-06-16T09:24:10Z
dc.date.issued	2021
dc.identifier.uri	http://10.250.8.41:8080/xmlui/handle/123456789/24153
dc.description.abstract	Using the DNA methylation data present in The Cancer Genome Atlas, we propose a new data preprocessing method where we use the caner driver genes to extract the relevant features from the data. After the preprocessing step we performed a feature extraction method where we selected top 50 features from each of the four sites of the human body. This method of feature extraction method yielded a comparable F-score against other studies while also reducing the overall space complexity of the problem	en_US
dc.language.iso	en_US	en_US
dc.publisher	SMME	en_US
dc.relation.ispartofseries	SMME-TH-578;
dc.subject	DNA Methylation, Driver Genes, mRMR, TCGA, Cancer, Feature Extraction, Machine Learning, Neural Networks	en_US
dc.title	Classification of Cancer using Epigenetic Markers in the Head and Neck	en_US
dc.type	Thesis	en_US