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Identification of Driver Genes in Glioblastoma Based on Single-Cell Gene Expression Data Utilizing the Concept of Pseudotime and Phylogenetic Analysis
, M.Sc. Thesis Sharif University of Technology ; Foroughmand Aarabi, Mohammad Hadi (Supervisor) ; Kavousi, Kaveh (Co-Supervisor) ; Zare Mirakabad, Fatemeh (Co-Supervisor)
Abstract
Genetic heterogeneity within a tumor, which occurs during cancer evolution, is one of the reasons for treatment failure and increased chances of drug resistance. Cancer cells initially derive from a mutated progenitor cell, resulting in shared mutated genes. Throughout the course of tumor formation and progression, the occurrence of new mutations is possible, leading to the generation of cancer cells with various mutated genes. An appropriate approach is to identify the sequence of mutations that have occurred in the tumor, which can be inferred from single-cell sequencing data. Singlecell data provides valuable information about branching events in the evolution of a cancerous tumor. In...