Honors Theses

Mary Lee

Affiliation

College of Engineering (James Worth Bagley), Agricultural and Biological Engineering

College

James Worth Bagley College of Engineering

College

James Worth Bagley College of Engineering

Department

Department of Agricultural and Biological Engineering

Department

Department of Agricultural and Biological Engineering

Degree

Bachelor of Science

Major

Biomedical Engineering

Document Type

Immediate Open Access

Abstract

Gene expression data is a compilation of gene activity expressed in a certain tissue. This data has the potential to help uncover genes associated with some disease, stimulus, and treatment. The Allen Brain Atlas has made available gene expression data describing the activity of genes in individuals and tissues related to aging, dementia, traumatic brain injury, brain cancer, and many other brain-specific conditions. This project uses statistical and information-theoretic metrics like Pearson correlation and mutual information to build gene co-expression networks, which are represented by nodes on a graph that correspond to a gene. The nodes are connected when they show significant co-expression relationship between their respective genes. These networks are constructed from samples exhibiting a variety of brain injury and disease, as well as those that appear typical. Gene co-expression networks were constructed from gene expression data of patients with traumatic brain injury, Alzheimer’s disease, and healthy patients. The resulting networks were visualized, and degree comparisons were performed. Those with significant and interesting differences were further researched for their function and possible role in developing Alzheimer’s disease.

Date Defended

11-25-2020

Thesis Director

Perkins, Andy

Second Committee Member

Nanduri, Bindu

Third Committee Member

Oppenheimer, Seth

Download

Share

COinS