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Hansiam Li 
Biochemistry student Hansaim Li works in with Professor Lei Xie at Hunter College, Computer Science Department.  In 2016, as a second-year doctoral student, Mr. Li published a peer-reviewed, first-authored publication in PLoS Computational Biology.  We congratulate Mr. Li on his publication, and asked him to discuss his research and impressions of the Biochemistry Ph.D. Program with us.

Why did you choose the GC Doctoral Program in Biochemistry?

During my undergraduate study of chemistry at Hunter College, I was interested in the chemical aspect of drug development. I also became interested in computational work, because I not only had good computer skills but also could see the relevance of computational work to drug development. Therefore, I pursued the bioinformatics component of the chemistry program. My goal has become to pursue drug development by integrating biochemical knowledge into an automated system that can accelerate drug discovery and development. I have had the opportunity to learn both biochemistry and computer science under the auspices of Dr. Lei Xie, an Associate Professor whose Ph.D. is in organic chemistry. Dr. Xie has been my mentor since I have been an undergraduate.  Dr. Xie’s goals with regard to drug development have become my goals and have prompted me to make the GC Biochemistry Ph.D. Program my top choice. 

In 2016 as a second-year doctoral student you published a research paper in PLoS Computational Biology. What were the major findings in this paper, and how were you able to publish so soon in your doctoral career?

Before I ender the Ph.D. program, I started learning computer programming languages (e.g. Matlab and R) that are fundamental skills necessary for my first paper. In the paper, we introduced a new computational tool  called REMAP for genome-wide drug off-target prediction. Compared to the state-of-the-art methods, REMAP is highly scalable in terms of memory and computational time with high degree of accuracy. It utilizes one of the famous machine learning techniques, called collaborative filtering, which is often used to recommend products to users based on their similarities. We are now developing a larger-scale (approximately 132 thousand chemicals against 553 thousands of protein targets across multiple organisms) application. Furthermore, we applied REMAP to drug repurposing, i.e. using FDA-approved drugs for new clinical indications. We have discovered that a drug originally developed for hypertension can be repurposed for the treatment of triple negative breast cancer and Alzheimer’s disease.

Tell us about your laboratory and your thesis research.

I work in the Computational Systems Biology and Polypharmacology Laboratory of Dr. Xie in the Computer Science Department at Hunter College. Our lab focuses on developing new methods and combines existing tools to systematically and computationally analyze various biological and biochemical data sets to understand molecular and cellular mechanisms of drug actions and genotype-phenotype associations. Our goal is to design precision medicines for complex diseases such as cancer and Alzheimer’s diseases. I use statistics and machine learning methods to predict unobserved relationships among different domains, such as chemicals, genes, diseases, and adverse drug reactions.

What are your greatest accomplishments since entering the GC Program in Biochemistry?

Working in a computational laboratory after the first year of graduate training in the traditional biochemistry curriculum is one of the best parts of the GC Ph.D. Program in Biochemistry. I greatly appreciate the openness of the program, which strengthens the program by expanding its scope.

What do you want to do after you get your Ph.D.?

I would like to secure a post-doctoral position after getting my Ph.D. I am open to working in the industry or academia.

What do you do in your free time?

I cook for my wife. Hopefully, it’s like a delicious chemistry experiment.

What surprised you most about being a CUNY doctoral student in Biochemistry?

I was pleasantly surprised by the diverse aspects of the courses for Biochemistry students. The first year includes topics from bench lab biochemistry to computational studies, including molecular dynamics and bioinformatics. After the first year, students can take courses that are not available in CUNY at other schools. Students have more opportunities, and schools save resources by removing duplicated courses from their offerings.