Sangmi Lee earned her PhD from the Korea Advanced Institute of Science and Technology (KAIST) in South Korea, where her research focused on the development and application of systems biology approaches for the discovery of cancer biomarkers and drug targets tailored to personalized cancer treatment. She developed computational methods to elucidate altered cancer metabolism and identify metabolism-based drug targets for high-risk cancer patients, employing network modeling, statistics, and artificial intelligence. These endeavors in deciphering the complex metabolic underpinnings of cancer lay the groundwork for developing therapies that are more effective and less toxic, thereby profoundly impacting patient care. Her work in computational biology, marked by a commitment to integrating multi-omics data and mathematical methodologies, underscores her continuous dedication to addressing medical challenges in cancer research. Sangmi is now focused on exploring the genomic underpinnings of cancer and its metabolism, drawing on her extensive expertise in bioinformatics, computational modeling, optimization techniques, and machine learning.
Systematic and Comparative Evaluation of Software Programs for Template-Based Modeling of Protein Structures.