Improving Disease Diagnosis and Treatments with Computer Models
Jake Chen puts his adventurous personality to work in the development of computational models and software tools that could save lots of lives one day. He studies numerous genes, proteins, and chemical compounds using a non-conventional “molecular systems biology” approach. This approach aims to collect complex associations among molecular entities and build computational network and pathway models. These complex biomolecular interaction network models can integrate genomics, functional genomics, proteomics, metabolomics, and published literature to help answer the question “how could genomics information help treat complex human disease?”
His translational research enables prioritization of human proteins as therapeutic drug targets or molecular biomarkers based on the protein’s new functional roles discovered at the new molecular network level. Results from this research are being used to design future generation, highly-specific cancer multi-protein biomarker panels that can help diagnose cancer, stratify cancer patients, monitor disease prognosis, and predict disease treatment outcomes. The knowledge also enables the discovery of novel therapeutic drugs and drug targets that can be customized to individual genetic predispositions.
The translational systems biology research paradigm reflects his unique interdisciplinary approach to problem solving, and draws on his diverse backgrounds in molecular biology, human genetics, biological data management, applied statistics, machine learning, information visualization, and high-performance computing. His research may transform future medicine in fundamental ways that bring the full benefit of the human genome project to the drug development and health care industries.
Professor Chen’s translational systems biology research is another outstanding example of how IUPUI's faculty members are TRANSLATING their RESEARCH INTO PRACTICE.