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  <title><![CDATA[CSE Distinguished Lecture: Orly Alter]]></title>
  <body><![CDATA[<div>
<p><strong>Speaker: Orly Alter</strong></p>

<p>USTAR&nbsp;Associate Professor of Bioengineering and Human Genetics,</p>

<p>Scientific Computing and Imaging Institute, Huntsman Cancer Institute</p>

<p>University of Utah</p>

<p>&nbsp;</p>

<p><strong>Thursday, March 29, 2018</strong></p>

<p><strong>Location:&nbsp;&nbsp;</strong>Klaus Advanced Computing Building, Room 1116E</p>

<p><strong>Time:&nbsp;</strong>11:00am &ndash; 12:00pm</p>

<p>------------------------------ -----</p>

<p>&nbsp;</p>

<p><strong>Title:</strong></p>

<p>Comparative Spectral Decompositions for Personalized Cancer Diagnostics, Prognostics, and Therapeutics</p>

<p>&nbsp;</p>

<p><strong>Abstract:</strong></p>

<p>I will describe the development of novel, multi-tensor generalizations of the singular value decomposition, and their use in the comparisons of brain, lung, ovarian, and uterine cancer and normal genomes, to&nbsp;uncover patterns of DNA copy-number alterations that predict survival and response to treatment, statistically better than, and independent of, the best indicators in clinical use and existing laboratory tests.&nbsp;Recurring alterations have been recognized as a hallmark of cancer for over a century, and observed in these cancers&rsquo; genomes for decades; however, copy-number subtypes predictive of patients&rsquo; outcomes were&nbsp;not identified before. The data had been publicly available, but the patterns remained unknown until the data were modeled by using the multi-tensor decompositions, illustrating the universal ability of these&nbsp;decompositions &ndash; generalizations of the frameworks that underlie the theoretical description of the physical world &ndash; to find what other methods miss.</p>

<p>&nbsp;</p>

<p><strong>Bio:</strong></p>

<p>Orly Alter is a USTAR associate professor of bioengineering and human genetics at the Scientific Computing and Imaging Institute and the Huntsman Cancer Institute at the University of Utah, and the principal&nbsp;investigator of an NCI Physical Sciences in Oncology U01 project grant. Inventor of the &ldquo;eigengene,&rdquo; she pioneered the matrix and tensor modeling of large-scale molecular biological data, which, as she&nbsp;demonstrated, can be used to correctly predict previously unknown physical, cellular and evolutionary mechanisms. Alter received her Ph.D. in applied physics at Stanford University, and her B.Sc.&nbsp;<em>magna cum&nbsp;laude</em>&nbsp;in physics at Tel Aviv University. Her Ph.D. thesis on &ldquo;Quantum Measurement of a Single System,&rdquo; which was published by Wiley-Interscience as a book, is recognized today as crucial to the field of&nbsp;gravitational wave detection.</p>
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<p>kristen.perez@cc.gatech.edu</p>
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