Predicting the influence of cancer drugs on human signalling network

• Main Author: Teo, I-Jen
• Other Authors: Sourav S Bhowmick
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science
• Online Access: https://hdl.handle.net/10356/175192
• Institution: Nanyang Technological University

Cancer is one of the largest disease burden in the world, being the second cause of death in people worldwide. Traditional methods such as radiotherapy and chemotherapy have been the mainstay of cancer treatment for decades. However, such non-targeted therapy methods have been known to cause severe side-effects. Targeted therapy has emerged as a promising approach to treat cancer, while promising to reduce side-effects. Targeted therapy targets genes in the human signalling network, which presents the opportunity to predict the influence of drug targets on the signalling network using graph traversal algorithms and other novel frameworks. Hence, this project proposes to implement such methods in a user-friendly and interactive graphical user interface for users to intuitively visualise the effects of a set of drug targets on the signalling network.