QBI - Seminar

Dynamic modeling of cancer signaling for precision medicine

November

09

10:00 AM-11:00 AM


The QBI/SBI Seminar Series on molecular networks of cancer and other diseases aims to facilitate collaborative relationships between scientists from both the US and Ireland. QBI and UCD recently signed a 5-year MOU to reinforce the links between scientists in San Francisco and Dublin, and enhance their collaborative ability to strengthen scientific research and innovation. Through this agreement, scientists will work together to identify opportunities to promote cooperative biosciences research and training activities. 

On November 9, the series will present Dirk Fey, an Ad Astra Assistant Professor for Anatomy at the School of Medicine of University College Dublin, who leads the Cancer Dynamics and Modeling group in Systems Biology Ireland. His aim is a quantitative understanding of cancer related signaling networks across the scales ranging from the intracellular to the organism level. He holds a PhD with “European” distinction from the University of Liege, Belgium, and a MEng in Engineering Cybernetics from the University of Stuttgart. Dirk’s career path included industry and several academic institutions, including BASF Ludwigshafen and Thomas Jefferson University, Philadelphia. He has won several scientific prizes, including the Irish Laboratory Award 2017 for Collaboration Achievement. 

In his talk, Dr. Fey will use mathematical models to gain insight into the dynamic, time-variant responses of cancer signaling networks, outline a mathematical framework for personalizing such models using tumor sample measurements from patients, and apply this framework to the JNK and p53 stress and DNA damage responses to predict neuroblastoma patient survival.

Talk title: "Dynamic modeling of cancer signaling for precision medicine"

Hosted by: Nevan Krogan, QBI | University of California, San Francisco 


Please click the link below to join the webinar:

https://ucsf.zoom.us/j/95595449719?pwd=YlBDd0FLUmxGNzJsL21USEFUQXNrZz09

Passcode: 405887

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