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	<title>2015Cianfrocco Cloud - Revision history</title>
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	<updated>2026-06-13T12:16:54Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
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	<entry>
		<id>https://3demmethods.i2pc.es/index.php?title=2015Cianfrocco_Cloud&amp;diff=2661&amp;oldid=prev</id>
		<title>CoSS: Created page with &quot;== Citation ==  Cianfrocco, M. A. &amp; Leschziner, A. E. Low cost, high performance processing of single particle cryo-electron microscopy data in the cloud. Elife, 2015, 4  == A...&quot;</title>
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		<updated>2015-05-29T06:27:11Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== Citation ==  Cianfrocco, M. A. &amp;amp; Leschziner, A. E. Low cost, high performance processing of single particle cryo-electron microscopy data in the cloud. Elife, 2015, 4  == A...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== Citation ==&lt;br /&gt;
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Cianfrocco, M. A. &amp;amp; Leschziner, A. E. Low cost, high performance processing of single particle cryo-electron microscopy data in the cloud. Elife, 2015, 4&lt;br /&gt;
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== Abstract ==&lt;br /&gt;
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The advent of a new generation of electron microscopes and direct electron detectors has realized the potential of single particle cryo-electron microscopy (cryo-EM) as a technique to generate high-resolution structures. Calculating these structures requires high performance computing clusters, a resource that may be limiting to many likely cryo-EM users. To address this limitation and facilitate the spread of cryo-EM, we developed a publicly available &amp;#039;off-the-shelf&amp;#039; computing environment on Amazon&amp;#039;s elastic cloud computing infrastructure. This environment provides users with single particle cryo-EM software packages and the ability to create computing clusters with 16-480+ CPUs. We tested our computing environment using a publicly available 80S yeast ribosome dataset and estimate that laboratories could determine high-resolution cryo-EM structures for $50 to $1500 per structure within a timeframe comparable to local clusters. Our analysis shows that Amazon&amp;#039;s cloud computing environment may offer a viable computing environment for cryo-EM.&lt;br /&gt;
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== Keywords ==&lt;br /&gt;
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== Links ==&lt;br /&gt;
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http://elifesciences.org/content/early/2015/05/08/eLife.06664&lt;br /&gt;
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== Related software ==&lt;br /&gt;
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== Related methods ==&lt;br /&gt;
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== Comments ==&lt;/div&gt;</summary>
		<author><name>CoSS</name></author>
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