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    <title>PhD-Thesis on icaoberg</title>
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      <title>Image-Derived Generative Modeling of Complex Cellular Organization in Both Space and Time</title>
      <link>https://www.andrew.cmu.edu/user/icaoberg/acknowledgements/2015-devin-sullivan-thesis/</link>
      <pubDate>Thu, 01 Jan 2015 00:00:00 +0000</pubDate>
      <guid>https://www.andrew.cmu.edu/user/icaoberg/acknowledgements/2015-devin-sullivan-thesis/</guid>
      <description>&lt;p&gt;Devin Sullivan&amp;rsquo;s PhD thesis in the Murphy Lab at Carnegie Mellon University extends generative statistical modeling of subcellular organization into three dimensions and across time. Building on the CellOrganizer framework, the work learns models of cell geometry, organelle morphology, and spatial distribution directly from fluorescence microscopy images — and introduces temporal modeling to capture how cellular organization evolves dynamically.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;h2 id=&#34;what-the-thesis-covers&#34;&gt;What the Thesis Covers&lt;/h2&gt;&#xA;&lt;p&gt;The thesis addresses a core challenge in computational cell biology: how to represent the spatial organization of a cell in a form that is both statistically rigorous and practically useful for downstream simulation. Key contributions include:&lt;/p&gt;</description>
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