Biomedical Informatics & Systems Modeling
Overview
At the Wallace H. Coulter Department of Biomedical Engineering, the Biomedical Informatics & Systems Modeling research area focuses on using computational tools, data science, and systems biology to uncover new insights into complex biological and clinical challenges.
Our interdisciplinary teams integrate bioinformatics, AI, and predictive modeling to drive discoveries in personalized medicine, disease modeling, and therapeutic innovation.
Research Focus
Our key areas of research include:
- Multi-Omics Data Integration: Linking genomics, proteomics, and metabolomics to disease mechanisms.
- AI and Machine Learning for Healthcare: Predictive models for patient outcomes and treatment optimization.
- Network and Systems Biology: Mapping and modeling biological pathways for therapeutic targeting.
- Digital Twins for Precision Medicine: Virtual patient models to simulate disease and treatments.
- Predictive Modeling and Simulation: Forecasting biological and clinical outcomes using advanced algorithms.
Recent research has included the study of how digital twin technologies use patient-specific data to simulate disease progression and test potential therapies, accelerating personalized treatment development.
Application Areas
Our research is transforming multiple healthcare sectors, including:
- Cancer Informatics: Predicting patient responses to immunotherapy using machine learning.
- Cardiovascular Modeling: Simulating heart functions to aid in surgical planning.
- Neuroinformatics: AI-based analysis of brain imaging for early neurological diagnosis.
- Drug Repurposing: Discovering new uses for existing drugs via computational screening.
Public Health Informatics: Modeling population data to predict and manage outbreaks
We provide access to cutting-edge computational and experimental resources, including:
- AI in Medicine Research Center: Machine learning models for diagnostics and therapeutics.
- Computational Biology and Bioinformatics Lab: Large-scale data analysis and systems modeling.
- Neuroinformatics and Brain Imaging Lab: Advanced imaging analysis for brain research.
We engage with a wide range of partners to ensure real-world impact:
- Emory University School of Medicine: Clinical informatics and patient outcomes
- Georgia Tech’s Institute for People and Technology (IPaT): Digital health innovation
- Industry Collaborations: Working with Philips, IBM Watson Health, Google Health, and more
