Combinatorial Algorithms for Tumor Phylogenetics
Thursday, March 30, 2017
to 5:00 PM
1070 Duncan Hall
Reception in DH 3092 at 3:30pm
Houston, Texas, USA
Cancer is a genetic disease, where cell division, mutation and selection produce a tumor composed of different subpopulations of cells with different complements of mutations. In the final stages of cancer progression, cancerous cells from the primary tumor migrate and seed metastases at distant anatomical sites. The cell division and mutation history of an individual tumor can be represented by a phylogenetic tree, helping guide patient-specific treatments.
In this talk, I will introduce combinatorial algorithms for constructing tumor phylogenies from bulk sequencing data, where the measurements are a mixture of thousands of cells. These algorithms are based on an extensive analysis of the combinatorial structure and complexity of the underlying problem statements. In addition, I will introduce a novel theoretical framework for analyzing the migration history of metastatic cancers, i.e. the structure of migrations in terms of their origin and destination anatomical sites. Using these methods, I analyze several cancers and identify tumor phylogenies and migration histories that are more biologically plausible than previously reported analyses.
Biography of Mohammed El-Kebir:
Mohammed El-Kebir is a postdoctoral research associate in the group of Ben Raphael at Princeton University. Mohammed received his PhD in Computer Science at CWI and VU University Amsterdam under the direction of Gunnar Klau and Jaap Heringa. He received the BioSB Young Investigator Award for his PhD thesis. In his research, he leverages a wide range of combinatorial optimization techniques to various questions in biology. Mohammed's current research focuses on tumor phylogenetics, where he develops algorithms for studying the progression of tumors.