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  <title><![CDATA[Immunoengineering Seminar Series]]></title>
  <body><![CDATA[<p><strong>Encoding and Decoding Specificity in Adaptive Immunity by Deep Learning</strong></p>

<p><strong>Sai Reddy, Ph.D.<br />
Associate Professor<br />
Department of Biosystems Science and Engineering&nbsp;<br />
ETH Zurich</strong></p>

<p>The ability to predict and correspondingly manipulate adaptive immune responses is highly valuable for biotechnology and medicine. To achieve this requires a greater molecular understanding of antigen selection and specificity by adaptive immune cells. In this I will explain how we are using deep learning to identify patterns of antigen-specificity in antibody responses following immunization. Deep neural networks are used to elucidate the antibody sequence space by generating thousands of novel and functional variants <em>in-silico</em>, highlighting how deep learning can be used to encode and decode specificity in adaptive immunity.</p>
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      <value><![CDATA["Encoding and Decoding Specificity in Adaptive Immunity by Deep Learning" - Sai Reddy, Ph.D. - ETH Zurich]]></value>
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      <value><![CDATA[2019-08-26T12:00:00-04:00]]></value>
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      <value><![CDATA[<p><a href="mailto:susan.thomas@me.gatech.edu">Susan Thomas</a>, faculty host</p>
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        <url>http://immunoengineering.gatech.edu/</url>
        <link_title><![CDATA[Center for Immunoengineering]]></link_title>
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        <url>https://bsse.ethz.ch/lsi/the-lab/People/STR.html</url>
        <link_title><![CDATA[Reddy profile]]></link_title>
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          <item><![CDATA[Parker H. Petit Institute for Bioengineering and Bioscience (IBB)]]></item>
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