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Jing ZhangOne of the newest faculty members of the Donald Bren School of Information and Computer Sciences (ICS) is Assistant Professor Jing Zhang, who joined the Department of Computer Science in July 2020. Zhang received her Ph.D. in electrical engineering and molecular and computational biology from the University of Southern California and completed her postdoc training in the Computational Biology and Bioinformatics Program at Yale University. She spent years working on ENCODE (Encyclopedia oDNA Elements), a project highlighted in the July 2020 issue of Nature. Zhang co-authored four of the issue’s articles, including “Expanded Encyclopaedias of DNA Elements in the Human and Mouse Genomes” and “An Integrative ENCODE Resource for Cancer Genomics.” The research for this work produced 5,992 new experimental datasets, all of which are available through the ENCODE data portal.

Here at UCI, Zhang is furthering her work to develop computational and statistical methods to better understand how genetic variations lead to certain diseases. And while moving to a new institution in the middle of a global pandemic has had its challenges, Zhang is excited to collaborate with new colleagues and students to develop methods that advance the field of genomics.

Can you talk about your research?
I worked in ENCODE for years, which is one of the pioneering consortiums using different types of sequencing technologies and annotating the human genome. We found that noncoding regions of the genome, which we thought were “junk DNA” decades ago, actually contain extensive gene regulation information. They host around 90% of disease-associated genetic variants.

This project was first launched in 2003, and we just completed the third phase of ENCODE. I finished my Ph.D. in 2013 and, in 2014, I started work in the ENCODE Data Analysis Center. Our goal was to annotate the human genome and link the genetic variations in the noncoding genome to human diseases and to explain how some genetic variants, which we thought were nonfunctional, can actually be disease causing. My work is focused on the tier-one cell types, for which we have the most experimental data. We constructed a gene-centric deep annotation resource to connect the noncoding elements to genes to better facilitate variant interpretation, because our current knowledge is mainly focused on the protein coding regions. Data from our work has been released to the community; you can go to the ENCODE website to download and use the data to facilitate your own studies. We showcased some application scenarios by finding cancer-associated risk factors.

Can you further discuss some of the real-world applications of your work?
Let me give you one example in precision medicine, which is especially important in cancer. Actually, cancer is a very heterogeneous disease — even breast cancer has different subtypes. Chemotherapy is a one-size-fits-all prescription for cancer patients. Recent therapeutic advances, such as immunotherapies, might offer new hope for cancer patients. However, these treatments work well on some patients but not others, so if we don’t know the subtypes or genetic basis of the type of breast cancer, success can be based purely on luck. It’s also an expensive and painful process for the patients. But if we can separate patients into different groups according to the molecular genetic basis of their disease, we can better suggest treatment types.

How did you go from studying electrical engineering to researching genetics?
I earned my undergraduate degree in electrical engineering. At the time, I was designing signal processing algorithms for antennas on our cell phones. It was a good time for multi-input, multi-output signal design for cell phones, and I had rigorous quantitative background training in signal processing. But then I came to the United States in 2008, which is when the age of sequencing technology was just getting started, leading to new discoveries in the field of genomics.

Originally, I thought genetic disorders were unfortunate yet very rare. But after attending some seminars, I was astonished to learn how prevalent genetic disorders can be. For example, many people are developing cancer, and my grandma passed away from breast cancer. However, if people know that they carry known genetic risk factors for a particular disease, they can act earlier —getting more frequent checkups, for example. Although engineering and genetics seem like two very different fields, math is actually the common tool that links these two areas together. When you are looking into these biological problems, you abstract them into mathematical models, and when you’re comfortable with those models, you’re able to make contributions.

What brought you to UCI?
When I was a graduate student at USC, I attended a regional conference at UCI — the Southern California Bioinformatics and Computational Biology Symposium. Since I was in the LA area, I already knew faculty members here. There is very strong computational biology and bioinformatics research going on throughout the whole department. And there are many very famous scientists in bioinformatics in UCI’s Computer Science Department. They are great scientists working to push this field forward.

What have been some of the challenges of moving to a new university during a global pandemic?
Well, I have to say, it’s been difficult. First of all, I was still living in New Haven (Connecticut) in February and March, when the East Coast was hard hit by COVID. I was hearing the ambulances running frequently outside of my apartment.

Also, I have a son who is four and a half. He’s very sweet, but he cannot go to school at the moment because of COVID. He has been staying home and taking online classes, which at times can be a mission impossible!

On top of that, we had to move our entire family to the West Coast, which we managed, but that was also quite challenging. Luckily, UCI has very good support for faculty so I already had rental housing before moving to Irvine.

To help people get to know you a little better, have you had a favorite TV show during the pandemic?
I guess my favorite TV show right now is “Car City” with my son! But other than that, it’s challenging because working from home means there’s no separation between life and work. My son is at home, running around all the time, and suddenly showing up in some of my Zoom calls!

In the future, I hope to have more chances to talk to people and to give presentations to let students get to know my lab, especially new graduate students. But luckily, I’m teaching a class in January — a project course in bioinformatics — so I look forward to having more interactions with students then.

— Shani Murray