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  <title><![CDATA[The School of Biological Sciences Spring 2023 Seminar Series presents Dr. Jorge Zanudo]]></title>
  <body><![CDATA[<div><strong>Jorge Zanudo, Ph.D.</strong></div>

<div><strong>Instructor (Dana-Farber Cancer Institute)</strong></div>

<div><strong>Computational Scientist (Broad Institute)</strong></div>

<p><em>Live via Zoom</em></p>

<p><em>Mathematical modeling and genomics of cancer networks: applications to drug resistance and transcriptional reprogramming</em></p>

<p>How does the intracellular network of cancer cells give&nbsp;rise to the changes in cell state that lead to drug resistance and transcriptional reprogramming? In this talk, I will tell you about how we have tackled this question using approaches from the fields of systems biology (by iterating mathematical models and experiments), mathematical modeling / network theory (by developing computational&nbsp;methods to analyze models), and cancer genomics (by analyzing multi-omic datasets with rich clinical annotations). In particular, I will talk about three projects, one for each of these approaches. In the first, we built and experimentally tested a model of the signaling network&nbsp;underlying resistance to PI3K-alpha inhibitors in breast cancer. In the second, we developed a network theory framework to identify controller nodes in a mathematical model. In the third, we identified genomic and transcriptomic drivers of resistance to CDK4/6 inhibitors in metastatic breast cancer. Finally, I will give a brief overview of my proposed research program on leveraging both mathematical modeling and cancer genomics to study drug resistance in breast cancer.</p>

<p>Host: Dr. Greg Gibson</p>
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