Yale and Boehringer Ingelheim have partnered to create a Biomedical Data Science Fellowship program for postdoctoral fellows. The program awards post-doctoral researchers a three-year fellowship that includes access to Yale’s robust computational resources, biomedical data repositories, and faculty expertise as well as Boehringer Ingelheim’s corporate labs, scientists, and executives.
“The collaboration with Boehringer Ingelheim is designed to create a world-class data science program that will drive development of novel methods and tools to analyze and interpret the many large and complex biomedical datasets that have been generated in recent years,” said Hongyu Zhao, Yale’s Ira V. Hiscock Professor of Biostatistics and a Yale professor of genetics, statistics and data science. Zhao is the program’s principal investigator.
With the program now in its second year, four new post-doctoral fellows – Rong Li, Dylan Duchen, Chuanpeng Dong, and Shubham Tripathi – began their work in September.
Li plans to analyze tumor, gene, and protein data in order to identify more specific subtypes of cancers for personalized patient treatment.
Duchen will use graphs to model immune cell profiles in individuals and identify which biological factors lead to better efficacy of treatments in patients.
Dong will use machine learning models to predict which paralog pairs (gene copies with different functions) could be effective in cancer immunotherapy.
Tripathi will create a mathematical model to determine which genes and cells directly affect immune responses, with the ultimate goal of being able to modulate this response.