Matthew G. Jones, PhD

About Me

I am an NCI K99/R00 Postdoctoral Scholar at Stanford University in Howard Chang's lab. Generally, I am interested in studying how tumors evolve over time, especially under various pressures exerted by the immune system and therapies. My work typically takes advantage of high-throughput sequencing assays (e.g., scRNA-seq and spatial transcriptomics), lineage-tracing technologies, and new computational tools and inference techniques.

My current research focuses on building more predictive models of tumor evolution, with a focus on how circular, oncogenic extrachromosomal DNA (ecDNA) reshape traditional rules of inheritance to accelerate tumor evolution and overcome targeted therapies. A key outcome of my research thus far is contributing to the discovery that ecDNA amplifications are often co-inherited during mitosis, leading to non-coding oncogenic amplifications and new therapeutic opportunities. Previously, I developed single-cell evolving lineage tracing technologies and computational tools. In this, I developed Cassiopeia, a software suite for reconstructing single-cell phylogenies from continuous CRISPR/Cas9 barcoding data. We used these tools to study how aggressive cancers evolve from a single transformed cell and eventually metastasize throughout a body.

In 2020, I spent the summer as a research intern at Google Brain Genomics working on deep learning methods for Electronic Health Record (EHR) data.

Previously, I completed my PhD in Bioinformatics at UC San Francisco and UC Berkeley advised by Jonathan Weissman and Nir Yosef. Before my graduate work, I studied Computer Science at UC Berkeley and worked in the Nielsen Lab on developing simulators for large admixture events. And before that, I grew up in a small town outside of Pasadena, CA where I was a tri-sport athelete and musician.