Plevritis Lab  
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Cancer Systems Laboratory (CSL)

Welcome to the Plevritis Lab

Cancer Systems Laboratory (CSL) views cancer as a complex system whose components can be reverse-engineered for the purposes of understanding the underlying mechanisms of cancer progression and identifying approaches for more effective cancer control strategies. Currently, our laboratory infers complex features of cancer progression through a variety of approaches that include: (1) reconstructing molecular networks of cancer, (2) integrating a diversity of molecular, pathological, imaging and clinical cancer data, and (3) mathematically modeling the progression of primary disease to metastatic stages in patients. Ultimately, our goal is to develop a comprehensive, multiscale view of cancer progression that merges these various approaches.

CSL brings together computational and biomathematical modelers, engineers, biological experimentalists and clinical researchers to ensure the biological and clinical relevance and translation. Meet the Team »

Sylvia Plevritis, PhD

Sylvia Plevritis, PhDDr. Plevritis is a Professor in the Department of Radiology in the Stanford School of Medicine. Dr. Plevritis holds a PhD in Electrical Engineering (Stanford, 1992) with concentration on MRI spectroscopic imaging of tumors. She also holds an MS in Health Services Research (Stanford, 1996), with concentration on the evaluation of cancer screening programs on reducing cancer mortality.  Dr. Plevritis is the Director of the Stanford Center for Cancer Systems Biology (CCSB), and the co-Section Chief of Information Sciences in Imaging at Stanford (ISIS).  

Dr. Plevritis is a Principal Investigator of the Stanford Cancer Intervention Surveillance Network (CISNET), which develops mathematical models of cancer progression and evaluates the effectiveness of mammography and MRI in screening for breast cancer and CT in screening for lung cancer.

News & Events

» CCSB 3rd Annual Symposium: Systems Biology of Cancer,
May 3, 2013

» RECOMB: Regulatory and Systems Genomics, with DREAM Challenges, Nov 8-12, 2013

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