Hi, everyone. My name is Evan Bai. I am now a Senior Research Scientist in Computational Genomics at Vertex Pharmaceuticals. I'm work in the field of Computational Genomics, which is that the intersection of biology and computational sciences. People usually arrive at this field by one of two paths. Either they are biologists who fell in love with computational programming, which is who I was, or computational scientists, who fell in love with biology. In terms of my own story. I've always been interested in biology, especially interested in genetics. I grew up in China, where in middle school and high school I was really interested and invested in biology. And then I came to the US at a small liberal art school called Ohio Wesleyan University, where I double majored in biology and chemistry. I really was very passionate about genetics as a concentration of my biology major. And during that time at my college study, I also did research all four years, to understand how plant root system uses gravity as cue to grow differently in response to a nutrient starvation. And that's how I fell in love with research. So after graduating from my undergrad, I wanted to pursue more about biomedical research. And that's when I started my PhD degree in genetics at Yale University, where I studied the underlying genetic causes for benign brain tumors to progress to become malignant. And since I was really passionate about biomedical research, this program was perfect for me because we actually studied actual tumor samples from patients to understand the genetic makeup. And during that time, I also had the fortune to participate in the Precision Medicine Initiative in Oncology at Yale, where I analyzed many brain tumor cases from patients at the Yale-New Haven Hospital. And in almost all of the cases, I could understand the underlying genetic cause for those brain tumors. However, in very few cases there are additional medicines we can give to treat the patients. So that really struck me that - so there's a huge bottleneck not in understanding the disease, but in developing medicines that could benefit patients. So that really solidified my interest to pursue a career in drug discovery. So during the last year of my PhD study, I did a summer internship at Gilead Sciences, a pharmaceutical Company on the West Coast. And I really enjoyed that experience. So after I graduated my PhD, I pursued drug discovery as a career. I interviewed at many biomedical companies. And while interviewing at Vertex. I really liked the energy from the people I met with, as well as the range of genomics questions I will get to work on. And both have indeed in the case. So now I have been at Vertex for almost 4.5 years.

That's a great question. So, my key responsibility now is that I am the Computational Genomics lead on two ongoing disease programs at Vertex. And I also managed one direct report who is also a computational biologist. When I say disease programs, I mean all the scientists working on the same disease at Vertex belong to the same disease project team, which includes biologists, epidemiologists, clinicians and even commercial strategists, all working together to identify key questions we need to address in order to develop a transformative medicine. So as the Computational Genomics lead, I identify areas where questions can be addressed using genomics. I then design, implement, and project manage relevant genomic studies. Once the genomic data is generated, I execute robust computational analysis to dive into the data in order to gain biological insight from it. Then I present and share the findings in a digestible way to the cross-functional disease project team. Again, where we together interpret the findings and align on what to do next? So it's a very iterative and cross-functional, collaborative process. I think it's a key part of my job. In terms of weekly work hours, back when we're still going to the office, I fortunately have a short commute. So I usually leave for work at 8 a.m. I get there around 8:30. I work till about 5:30 in afternoon. It includes usually one hour lunch break and our coffee break somewhere in afternoon. Or tea break for me. I came home and then I do my evening routines - exercise and dinner. Usually I spend one hour at night to check some emails. Reply some emails I didn't get to during the day. Usually, I don't work too many hours on weekends but (there are) always exceptions to keep deadlines and stuff. I think that changes. Since this year, I become a co-chair of one of the employees resource networks at Vertex. So that actually has been a lot of very exciting work. So that adds about two more hours to my day, usually working on the employee resource initiatives.

Scientists, compositional biologists, or bioinformaticians usually use programming languages such as R. It's a statistical programming language. Or python. I think it's more important to master one than trying to learn too many languages. We also have to be familiar with the the LINUX or UNIX programming system and have experience working with high-throughput computing environment. In addition to that, experience was workflow language and cloud computing is usually a plus. But in addition to those specific computational skills, I think a proven track record, usually from someone's PhD research, in the analysis, visualization, and interpretation of genomic data. Usually is a key component as well.