"Please give a brief self-introduction first, and then talk about your understanding of computational biology."

“I heard that you are quite interested in computational biology, which is a cutting-edge field in recent years. Some people from your department went to UCSB to pursue a PhD in computational biology.”

Zheng Li looked directly into the other person's eyes:

"Professor Li, I am a freshman in the base class of the School of Mathematics. I am currently in the first semester of my freshman year and have completed the university-level professional courses in basic mathematics."

"During my studies, I gradually discovered that I am very interested in biology. The reason I chose computational biology is that it can be well integrated with what I studied in my undergraduate studies."

"I have a good grasp of both R and Python languages, and I also have a general understanding of data structures and algorithms in computer science."

"My understanding of computational biology is to analyze biological problems through mathematical models and quantitative analysis."

"In the earliest days of physics, experiment and theory were two sides of the same coin in physics research. After the birth of quantum mechanics, many phenomena could not be observed experimentally and could only be proven to exist theoretically."

"For example, dark matter. Humans can prove its existence, but cannot observe it, let alone capture it."

"Biology has always been troubled by experiments. You have to use experimental results to prove the correctness of the theory. Computational biology is the direction that biologists hope to develop in order to break through this dilemma."

"Solve biological problems through mathematical models and quantitative analysis methods."