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Sci. Signal., 4 February 2014
Vol. 7, Issue 311, p. pc4
Science Signaling Podcast: 4 February 2014
John Cijiang He1,3, and
Annalisa M. VanHook4
1 Department of Pharmacology and Systems Therapeutics, Department of Medicine, Mount Sinai School of Medicine, New York, NY 10029, USA. 2 Systems Biology Center New York, Department of Medicine, Mount Sinai School of Medicine, New York, NY 10029, USA. 3 Division of Nephrology, Department of Medicine, Mount Sinai School of Medicine, New York, NY 10029, USA. 4 Web Editor, Science Signaling, American Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005, USA.
This Podcast features an interview with Ravi Iyengar and John He, authors of a Research Article published in the 4 February 2014 issue of Science Signaling, about using network modeling to predict strategies for repairing kidney damage. Kidney damage is often characterized by changes in the morphology of podocytes. The highly specialized morphology of podocytes is critical for the kidney's ability to filter waste products out of the blood without allowing proteins and other large molecules to leak from the blood into the urine. A group led by Ravi Iyengar and John He identified changes in protein abundance that were associated with damaged kidneys and used computational methods to predict drug targets for restoring normal podocyte morphology and function.
Citation: R. Iyengar, J. C. He, A. M. VanHook, Science Signaling Podcast: 4 February 2014. Sci. Signal.7, pc4 (2014).
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