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The Redox Systems Biology Lab - Kemp

Biomedical Informatics and Systems Modeling

Biomedical Informatics and Systems Modeling covers a diverse field at the intersection of computational science, biology and medicine. The overarching goal is to develop machine learning and artificial intelligence methods, mechanistic models, and simulations to describe observed biological phenomena and data, derive new biological insights, and ultimately translate to impacts on scientific discoveries, human health, and patient care. The field uses methodologies in computer science, statistics, electrical engineering, and informatics to integrate experimental and clinical data, derive knowledge, and make actionable decisions. Typical applications include bioinformatics, systems biology, clinical informatics, computational neuroscience, image analysis, precision medicine, and immunoengineering, all of which are highly synergistic to other research areas in the department. 

Latest News on Biomedical Informatics and Systems Modeling research

Kemp lab uses genome-scale modeling to understand tumor metabolism and predict tumors’ responses to radiation therapy

BME's May Wang leading three of the seven projects in new initiative to improve lives of pediatric patients

Undergraduate researchers help Cassie Mitchell turn millions of studies into actionable insight