Building scalable computational tools to decode molecular processes in cancer, child health, and development

Our bodies contain unique molecular markers that can reveal important information about our health, but analyzing these markers is challenging due to the vast amounts of noisy and complex data. Our research aims to develop new computational tools that make it easier and more cost-effective to interpret these molecular signals, with two main goals: First, we’re creating methods that could be applied to detect cancer earlier through blood tests by detecting fragments of DNA from various organs in the body. Second, we’re studying how environmental factors in early life influence prenatal and long-term health by examining what causes these molecular changes. We will create user-friendly software tools that enable scientists and doctors to analyze molecular data more effectively and affordably. This could lead to better cancer screening tests and help us understand how early-life experiences affect health. We’ll also evaluate how well these tests work in different healthcare settings to ensure they benefit diverse patient populations. Ultimately, our work will advance both cancer detection and our understanding of child development while making cutting-edge molecular analysis more accessible to the research community.