Advanced statistical modeling for phenotype prediction based on high throughput genomic data

Date

2015

Authors

Ma, Chifeng

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Abstract

The detection and prediction of phenotype is one of the primary goals of evolutionary genetics. This thesis focus on the application of advanced statistical modeling for phenotype detection and prediction as well as classification. In chapter two, the general algorithm for phenotype detection and prediction is surveyed. In chapter three, four and five, three application of advanced statistical modeling for phenotype prediction is demonstrated including a drug discovering study using connectivity map Microarray dataset; a cancer subtype classification study using TCGA and independent Microarray dataset; and a breast cancer differential methylation detection study. In chapter six, the conclusion is drowned and the future work is proposed.

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Keywords

High-throughput Genomic data, Phenotype Detection, Statistical Modeling

Citation

Department

Electrical and Computer Engineering