Jeremiah Wala

Jeremiah Wala

Advisor: Rameen Beroukhim
Jeremiah Wala

What is your academic background? What research experience did you have before grad school?

 

I studied physics at Cornell and my favorite courses were in quantum mechanics. I also completed my pre-medical requirements and took courses in medical imaging. My undergraduate research experience was in a nanotechnology lab where I worked on applications of electrospun polymer microfibers. I also spent a year working on pulmonary vasculature detection in low-dose chest CT scans.

 

What is your research area and why is it exciting?

 

I studied rearrangements in the cancer genome, a topic which has been both fascinating and highly applicable to clinical oncology. The cancer genome has an extraordinary way of twisting itself into knots through rearrangements, deletions and amplifications, and each genome is different than the next. Putting together the pieces is a computationally interesting problem because it requires thinking about string algorithms, topology and a wide array of sequencing technologies. In particular, I was interested in piecing together mult-part rearrangements, where replication would "skip" around from chromosome to chromosome. We found these events contributed to fusions and oncogene amplifications in numerous adult and pediatric tumors. We provided a tool (SvABA) for systematically identifying these events (among others) across the genome. We also looked at rearrangements across 2,600 cancer genomes and found recurrent events that were either too small to be previously seen, or were copy-neutral, and not previously not seen with traditional copy-number array techniques. As the number of whole-genome cancer and germline genomes continues to grow, I looking forward to working on deciphering the impact of rearrangements on gene expression, cryptogenic germline conditions, and as drivers in tumor genomes.

 

Why did you choose BIG?

 

As a program with a particular focus on computational approaches in biology, BIG provided the opportunity to learn from other a small group of peers with incredible talent and focus in these areas, but in an environment that was large enough to accommodate any research interest. The core course curriculum was a great mixture of computation, statistics, and fundamental genetics and molecular biology, in addition to courses focused on reading computational biology papers. Additional courses are available in virtually any topic one could want (immunology, microbiology, medical imaging, machine learning, etc).

 

What was your favorite class and why?

 

HST 508 Quantitative Genomics: We derived the dynamics of populations genetics using only first-principles and a blackboard. Provided a great framework for thinking about de novo variation, GWAS, evolution and tumor heterogeneity.

 

How do you like living in Boston? What do you do when you are not working?

 

Boston is an incredible city. We really enjoy going to the beaches on the North Shore, hiking in the mountains in New Hampshire, and trying out new restaurants in Cambridge and Boston.

 

What advice would you give to college students who are interested in a PhD in genomics/bioinformatics?

 

High-impact genomics research really requires both cellular biology knowledge and a strong computational base. You don't have to start with both, but if your focus has been in biology, building a toolkit of abilities in machine learning and programming (typically R/Python + a compiled language like C++ or Java) will be key. If you have great computational skills, push yourself to take advantage of biology coursework to make sure you can apply your skills to relevant questions in biology and medicine.

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