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Increasingly complex biological problems and extremely large biological data sets have necessitated new approaches to answer many of today’s current research challenges and tackle emerging questions in biology not amenable to traditional approaches.  As one of the fields in the “New Biologies”, Computational and Systems Biology (CSB) encompasses an interdisciplinary approach that harnesses the power of computation and systems-level analyses to formulate and solve critical biological problems.  These research programs within CSB also synergize and collaborate with the extensive basic and clinical research programs at the University of Pittsburgh and across the globe.  Concomitant with our research foci, CSB is also a leader in educating and training all levels of emerging and nascent scientists, who will continue this work and identify and tackle new biological problems of the next generation.

Machine learning model can help reduce follow up screenings to 28% of people with benign nodules
A new machine learning model, developed in the Benos lab, can help reduce the unnecessary follow up screenings to people with benign nodules detected in low-dose CT scans by 28%. (read more)

 

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