The CTSI Biomedical Modeling Core's mission is to make computational approaches for prediction accessible and useful to a wide variety of clinical and translational investigators.
Computational and mathematical models allow researchers to simulate complex systems and discover patterns and novel predictions. The use of computational approaches is already commonplace in the physical sciences and engineering, but relatively few biomedical researchers take advantage of the opportunities provided by modeling. The pace of research translation to the clinic and community can improve by implementing modeling at appropriate points of the research spectrum to enhance efficiency and to discover patterns and novel predictions not appreciable without sophisticated biomedical computational approaches. The Biomedical Modeling Core exists to embed modeling in the translational research workflow through communication, collaboration, training, and pilot support of new partnerships.
The Core aims to introduce translational investigators to the language, rationale, tools, and processes necessary to integrate multiscale biomedical computational modeling into their research. Investigators at the bench, bedside, and community may not currently recognize the benefit of biomedical computational modeling, and many mathematical modelers lack awareness of or access to the copious translational data produced at Pitt. The Core can introduce investigators to the modeling community in Pittsburgh, which includes researchers with expertise spanning the entire translational research spectrum, including molecular modeling, cellular systems biology, genomic and proteomic association studies, computational pathology, tissue and organ modeling, personalized medicine, and public health modeling. The modeling and translation communities would both benefit from understanding each other’s needs and capabilities.
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If you received services through the Clinical and Translational Science Institute (CTSI) that contributed to the scientific knowledge disseminated in publications, please acknowledge CTSI with the following citation:
The project described was supported by the National Institutes of Health through Grant Number UL1TR001857.