A third-year bioinformatics student used programming and machine learning to model and predict the efficacy of drugs in cancer cells and patients, making data the key to decoding life. Hillhouse is also cultivating more interdisciplinary explorers of "computation × life sciences".
During holidays, graduates often return to Hillhouse to visit their professors. Those students who once neglected their meals and sleep for video games have now grown into explorers on the path of scientific research or engineering. Some are working closely with top professors in their fields, while others are dedicating themselves to cutting-edge research in bioinformatics.
Today, we'll mainly talk about a bioinformatics graduate, currently a junior, who shared his research with us: using programming and machine learning techniques to build models and predict the efficacy of drugs in cancer cell lines and different cancer patients. In his hands, data is no longer just cold numbers, but the code to life mechanisms.
1. What is bioinformatics?
Bioinformatics is precisely such a discipline that connects "code and life." It integrates biology, computer science, statistics, and artificial intelligence, using computational analysis to understand genomes, protein structures, disease mechanisms, and drug responses, making it a core field in the digital life era.
By leveraging massive amounts of modern data, bioinformatics can predict protein structures, perform gene sequencing, predict new drug structures, and develop targeted therapies at low cost, without requiring extensive and costly laboratory experiments. It has enormous application potential in the pharmaceutical and medical fields, and a promising market outlook.
2. What academic foundation is needed to study a popular major?
At Hillhouse, a growing number of students are choosing the interdisciplinary path of "Digital Computing × Life Sciences." Applying to this program requires planning and preparation along these two main academic tracks during high school:
- Mathematics, Statistics, Modeling, Programming and AI
Starting with skipping grades in math in grades 8 and 9, Hillhouse students have consistently been ahead in their academic foundation courses. While building a solid foundation in mathematics at school, they also receive introductions to mathematical modeling and AI. In a data-driven context, modeling and AI skills can be readily transferred to business (business analytics modeling, asset pricing prediction), biology (gene sequencing, protein structure analysis, targeted drug development), and even traditional humanities subjects such as history and literature studies .
- Science, biology, biology competitions, biological research
Our students not only learn knowledge through courses, but also cultivate their interest in biology through hands-on activities such as visiting botanical gardens , exploring urban marshes , and conducting dissection experiments . This leads to biology competitions and research. Combining fundamental biology with modeling , students learn systems biology and gene network models , developing their abilities in population dynamics simulation and ecological modeling through experiments and competitions.
- Economics and business competitions
Our economics and business students begin studying macroeconomics and microeconomics in 10th grade. They actively take business and entrepreneurship courses and participate in business clubs . Building on this foundation, and combining mathematical modeling and AI tools, they can conduct research on popular economics, finance, and business topics such as data-driven business analysis , market analysis , and quantitative model forecasting .
We will train more and more students to learn modeling in the field of statistics, while strengthening their exposure to life sciences and conducting in-depth research in biology, physics, and chemistry...
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