Honors Theses
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
Recommended Citation
Lee, Mary, "A Topological Analysis of Gene Co-Expression Networks from Brain Data" (2020). Honors Theses. 140.
https://scholarsjunction.msstate.edu/honorstheses/140