Joint CMU-Pitt Ph.D. Program in Computational Biology
Carnegie Mellon University
Understanding Tumor Composition and Evolution Through Geometric Models
Despite rapid progress in the understanding and treatment of disease over the course of the past 100 years, diagnosis and treatment of cancer has become a focal point for basic science research. As a result, advances have been made in quantifying the myriad changes in tumor genomes, transcriptomes, epigenomes, and metagenomes as compared to healthy tissue.
Specific to the work of this thesis, technical advances have led to more robust quantification of RNA expression states via RNA-seq, and DNA copy number quantification via DNA-seq. These approaches allow for the measurement of the state of tens of thousands of genes in a sample. Moreover, the enhanced quantification has led to understanding the existence of heterogeneity among tumors.
Thesis Committee: Russell Schwartz (Advisor) Adrian Lee Robin Lee Jessica Zhang Jian Ma