Yupeng He, PhD, is a computational biologist, who applies statistical methods on biology data to improve our understanding of biology problems. He received his PhD in Bioinformatics from UCSD where he studied the dynamics of DNA methylation in the Ecker Lab at The Salk Institute. Since graduating, he joined Guardant Health as a Bioinformatics Scientist and has risen the ranks to his current position as Manager in the Bioinformatics group to help develop liquid biopsy technology that detects cancer at an early stage. 

Can you describe your academic and professional background? What path led you to pursue this field? 

I love dealing with numbers growing up and became interested in biology in my high school. Naturally, I chose biology as my major in my undergrad in the sophomore year, I decided to stretch myself and picked mathematics as my minor based on my interest. Though in hindsight what I learned by taking this minor is not very useful, it helps me overcome any fear in digging into many math problems I encountered. 

It did not take long for me to decide to pursue an advanced degree as I enjoyed digging into biology problems to understand what is behind them. However, I did not have good hands in doing wet lab experiments. Meanwhile, I was extremely interested in modeling and data analysis. When I learned about bioinformatics, I was deeply fascinated by the idea of using computational tools to solve biology questions and I knew it was where I would be heading. It was around 2009 when bioinformatics was then still an emerging field.

I then joined a bioinformatics lab and was fortunate to meet a great mentor. He kindly pointed me to a challenging problem of predicting genes from just DNA sequence and is very supportive. This project led to a publication. To further pursue my interest in bioinformatics, I applied to the bioinformatics PhD program at UCSD and eventually landed at Ecker lab to study the landscape and function of DNA methylation (a chemical modification on DNA). 

After grad school, I was at the crossroad of staying in academia and exploring industry. I decided to learn about something different. I applied to bioinformatics jobs in companies and here I am in Guardant Health.

How did you find this particular position, and what was the hiring process like? Is there a typical structure for this in your field? 

When I was applying to industry jobs in mid 2017, there were not many bioinformatics scientist openings. Also, I decided to move to the San Francisco Bay Area due to family reasons. I only searched for jobs in that area. After some homework, I found a few promising fields: liquid biopsy (analyzing floating DNA in the blood), immunoncology (immune + cancer research) and direct-to-consumer genetic testing (e.g. 23andMe). In these fields, tons of data are generated to address important health care problems, providing great opportunities for bioinformatics research. I reached out to people I know in industry to learn about openings in these fields. And I learned about Guardant Health. After a few phone interviews, Guardant Health invited me to an on-site interview and eventually offered me a position. 

A typical interview process of a research position in biotech consists of a few rounds:

• Usually, as the first round, the recruiter (usually from the human-resource department) will call you to ask about your background, interests, the positions you are looking for, and importantly, your visa status and when you can start. This round is generally not technical but it can still be challenging because some recruiters usually ask a few behavior questions. 

• Second round is from the hiring manager (leader of the group you are interviewing for) to technically evaluate your background/knowledge and whether your personality will be a good fit to the team (culture fit). This may involve some technical tests either through phone or some online tools. There could be a third round of phone interview to further evaluate your technical skills. 

• If you pass the phone interviews, the company will invite you to an half-day/full-day on-site interview (or a video interview during a pandemic). You will be asked to give a 30-45 minute presentation to introduce yourself and your work. Then, you will talk to a few members in the team in a series of 1 on 1 interviews. They will evaluate different aspects of your skills, your interests, and your fit to the team. 

• The on-site interview is usually the last round but there could be one additional phone interview, usually from a senior person in the company. 

Can you tell us about your current responsibilities? What is a typical day or week like in your role?

I am spending ~30% of my time on doing management/mentorship/communication/coordination and ~70% on technical problems. My team is working on a product to detect cancer at an early stage. My current position requires my involvement in multiple aspects of the product development such as the designs and analysis of wet lab experiments, statistical modeling of our data and planning of future products. This involves intensive communication with members from different subteams, which is especially necessary during the pandemic. A typical week of mine includes a series of meetings such as 1 on 1 meetings with members in the team to discuss technical problems we encountered and career development, discussion on very challenging technical issues in data analysis and statistical models we are building, and meetings with people from different subteams to discuss data and experiment plans. For the rest of the time, I code and build machine-learning models to address challenging technical problems.

What do you enjoy about your current job and work environment? 

What attracted me the most when I was interviewed at Guardant Health was the people in the team. After being in the company for more than 2 years, I still very much enjoy working with them. It is a team with super smart people with different backgrounds (molecular biology, statistics, computer science, software engineering, bioinformatics and physics) and it is also an inclusive community that people with different personalities can easily fit in. It is a great experience working with excellent people towards a common goal and at the same time learning from each other.

What are some of the challenging aspects of your job? Is there anything you wish you had known about your job or industry before joining?

One of the challenges I am fighting with is to stay open minded and keep listening to different opinions. It is very easy to be overconfident, become ignorant about our blind spots and meanwhile be defensive to different opinions. That is how our brain works and it will take effort to overcome the tendency to be overconfident (if you are interested in how our brain works, I recommend reading the book Thinking, Fast and Slow). I wish I could have learned about this when I started my job. 

Do you have any professional plans for the future? What are some future career paths that could open up for someone in your position, 5-10 years down the road?

I enjoy working on challenging technical problems and helping people grow in their career. I want to be a technical manager, who has a strong technical background and at the same time manages a team. Going down the road, I see myself as a manager, a tech lead, a director, an advisor/consultant or a C-level position to be in charge of the development of a product or even a company. 

What’s changing in your industry? Are there any future trends we should be aware of?

Liquid biopsy or cell-free DNA is a booming industry. This also means that this field is changing rapidly. The products or services in the field are under strict regulation (by for example FDA). However, since this is a new territory, the regulatory landscape and guidelines from regulatory bodies change quite a lot. For example, the recent decision draft for liquid biopsy CRC screening products from CMS guides the acceptance criteria of new products and has a dramatic impact on the market.

From the technical side, while genetic mutations remain still a major biomarker for early cancer detection, many companies realize the importance of epigenomic markers like DNA methylation and fragmentation patterns. Many new experiment assays/techniques have been developed to quantify these new markers. This is just about DNA. There are also efforts looking into RNA signal and protein signal. Integrating different signals involves careful computational modeling. The future products will be the combination of what is called multi-analyte assays, involving many biomarkers, and advanced machine learning techniques. 

What activities, internships, or organizations would you recommend someone get involved with to help them break into this field?

UCSD has strong biology and bioinformatics programs and many alumni are working in the biotech industry. Seeking help, information and even internal referral from alumni would save you a lot of time and efforts. Besides, many companies such as Genentech and Illumina have internship programs and these are great opportunities to get involved in and accumulate experience in industry research. Most importantly, being technically savvy is the prerequisite of getting a research position. Many labs in UCSD are working on frontier technologies that are being developed into products in biotech companies. One example is next-generation sequencing (NGS). Having research experiences in labs working on or using NGS will dramatically increase the chance of getting a position in a company like Illumina. 

Is it common for people in your field to have a scientific/academic background (i.e. have PhDs)? Can you think of any advantages or disadvantages someone with a PhD might experience while pursuing or working in your field?

For research & development (R&D) positions in biotech companies, having a PhD is a significant advantage. It is often required for people to have a PhD degree in order to succeed in such positions. Some positions even require postdoctoral research experience. This is determined by the nature of the position.

I think PhD and postdoctoral experience help in at least two aspects. Technically, to get a PhD, one usually needs to dig into the bolts and nuts of a specific topic for years and eventually become an expert in that field. If what you are good at matches what the position needs, you would be much more competitive and capable than people who don’t have such experience. The reason behind this is that research and product development often are inventing or optimizing an assay or a computational algorithm/model, and digging into almost every technical detail. If you already know about the cutting edge techniques, common mistakes/issues and the fixes and tools/resources for development/analysis in your PhD, you can make significant contributions. These experiences and skills are not impossible to acquire such knowledge/skills without getting a PhD but it is very difficult and it rarely happens. Second, research is exploring unknowns and drawbacks are very common. The challenges in grad school would make people mentally prepared for such drawbacks. 

Do you have any final words of advice for those navigating these career questions? Is there anything you would have done differently given what you know now? 

There are many decisions to make in our career. When facing choices, I found it very useful to always take a step back and think about the career path in the next 3-5 years, 10 years or even longer. This would help us understand what we actually face. For example, when choosing between two different job offers, the position aligned with your career path is usually a much better choice in the long run compared to the position that does not match what you want to do but pays more. Moreover, you will get paid later and eventually earn more by staying on the right career path.