PhD Dissertation Defense Announcement of Forough Firoozbakht:"Identifying Network Biomarkers for Each Breast Cancer Subtypes Along With Their Effective Single and Paired Repurposed Drugs Using Network-Based Machine Learning Techniques"

 

Date: Tuesday September 6, 2022 

Time:  10:00 AM – 1:00 PM 

Passcode: If interested in attending this event, contact the Graduate Secretary at csgradinfo@uwindsor.ca with sufficient notice before the event to obtain the passcode.

 

Breast cancer is a complex disease that can be classified into at least 10 different molecular subtypes. Appropriate diagnosis of specific subtypes is critical for ensuring the best possible patient treatment and response to therapy. We propose a machine learning framework that can be used to identify network biomarkers and driver genes for each specific breast cancer subtype. Our results show that the resulting network biomarkers can separate one subtype from the others with very high accuracy. We also propose an integrated approach that can best capture knowledge (and complex relationships) contained within and between drugs, genes and disease data. A network-based machine learning approach is applied thereafter by using the extracted knowledge and relationships in order to identify single and pair of approved or experimental drugs with potential therapeutic effects on different breast cancer subtypes. 

 

Breast Cancer, Drug repurposing, Network-based approach, Drug-disease network, Protein-Protein Interaction  

PhD Doctoral Committee:  

Internal Reader:  Dr. Jianguo Lu 

Internal Reader:  Dr. Dan Wu       

External Reader: Dr. Esam Abdel-Raheem, Department of Electrical and Computer Engineering 

External Examiner: Dr. Abdoulaye Banire Diallo, Department of Computer Science, Université du Québec à Montréal 

Advisor(s): Dr. Luis Rueda , Dr. Alioune Ngom 

Chair: Dr. Nickolas Eaves, Faculty Member, Department of Mechanical, Automotive, and Materials Engineering