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<p class="x_MsoNormal" style="margin-bottom:12.0pt"><span style="font-size:13.5pt; font-family:"Arial",sans-serif,serif,"EmojiFont"; color:black">Dear all,<br>
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<p class="x_MsoNormal" style="margin-bottom:12.0pt"><span style="font-size:13.5pt; font-family:"Arial",sans-serif,serif,"EmojiFont"; color:black">Nvidia is holding a webinar event which is of general interest to the EM community. Led by MIT and NYSBC, the webinar
will cover the general problem and importance of object detection in cryoEM along with a robust solution for particle picking, Topaz. Please see the link below to register.</span></p>
<p class="x_MsoNormal" style="margin-bottom:12.0pt"><span style="font-size:13.5pt; font-family:"Arial",sans-serif,serif,"EmojiFont"; color:black"><a href="https://info.nvidia.com/ai-cryoem-data-selection-reg-page" class="OWAAutoLink" id="LPlnk446942" previewremoved="true">https://info.nvidia.com/ai-cryoem-data-selection-reg-page</a><br>
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<p class="x_MsoNormal" style="margin-bottom:12.0pt"><span style="font-size:13.5pt; font-family:"Arial",sans-serif,serif,"EmojiFont"; color:black">Date: Tuesday, May 14, 2019</span></p>
<p class="x_MsoNormal" style="margin-bottom:12.0pt"><span style="font-size:13.5pt; font-family:"Arial",sans-serif,serif,"EmojiFont"; color:black">Time: 9am – 10am US PT; 12pm <span style="font-size:13.5pt; font-family:"Arial",sans-serif,serif,"EmojiFont"; color:black">–</span>
1pm ET; 5pm <span style="font-size:13.5pt; font-family:"Arial",sans-serif,serif,"EmojiFont"; color:black"><span style="font-size:13.5pt; font-family:"Arial",sans-serif,serif,"EmojiFont"; color:black">–</span></span> 6pm BST<br>
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<span id="ms-rterangepaste-end"></span>Description</span></b></p>
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<div>Single particle cryo-electron microscopy (cryoEM) is an imaging technology that allows direct observation of proteins in native and near-native states in atomic detail. However, determining the structure of a protein from projections captured by the EM
requires collecting millions of examples. <br>
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By leveraging positive-unlabeled learning, we can use a small number of example protein projections, provided by the user, to train a neural network to detect proteins of any size or shape. Topaz, the implementation of this framework, can detect significantly
more proteins than all other software tested while also minimizing manual labeling required by the user. Furthermore, the positive-unlabeled approach to object detection is broadly applicable to other microscopy domains.</div>
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<p class="x_MsoNormal"><b><span style="font-size:13.5pt; font-family:"Arial",sans-serif,serif,"EmojiFont"; color:black; background:white none repeat scroll 0% 0%">By attending this webinar, you'll learn:</span></b><span style="font-family:"Arial",sans-serif,serif,"EmojiFont""></span></p>
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<span>CryoEM image collection and processing procedures</span></li><li class="x_MsoNormal" style="color:black; line-height:18.0pt; background:white">
<span style="font-size:12pt; font-family:"Arial",sans-serif,serif,"EmojiFont""></span><span>Particle picking in cryoEM images with Topaz using positive-unlabeled learning</span></li><li class="x_MsoNormal" style="color:black; line-height:18.0pt; background:white">
<span><span>Prospects in the automation of cryoEM</span><br>
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We look forward to your attendance.</div>
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Kind regards,</div>
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Tristan Bepler</div>
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Alex Noble<br>
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