Identifying Cancer-related Genes Via Network Feature Learning and Multi-Omics Data Integration, M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor)
Abstract
The highly developed biological data collection methods enable scientists to capture protein-protein interaction (PPI) in the human body, which could be analyzed as biological networks such as protein-protein interaction networks. These networks reveal essential information about the biological process in human cells and can be used to identify genes associated with cancers. Effectively identifying disease-related genes would contribute to improving the treatment and diagnosis of various diseases. Current methods for identifying disease-related genes mainly focus on the hypothesis of guilt-by-association and do not consider the global information in the PPI network. Besides, most methods pay...
Cataloging briefIdentifying Cancer-related Genes Via Network Feature Learning and Multi-Omics Data Integration, M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor)
Abstract
The highly developed biological data collection methods enable scientists to capture protein-protein interaction (PPI) in the human body, which could be analyzed as biological networks such as protein-protein interaction networks. These networks reveal essential information about the biological process in human cells and can be used to identify genes associated with cancers. Effectively identifying disease-related genes would contribute to improving the treatment and diagnosis of various diseases. Current methods for identifying disease-related genes mainly focus on the hypothesis of guilt-by-association and do not consider the global information in the PPI network. Besides, most methods pay...
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