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<p class="MsoNormal" style="text-align:center; background:white" align="center"><b style=""><span style="font-size:14.0pt; line-height:115%" lang="EN">2020 NIH iDASH Secure Genome Analysis Competition and Workshop</span></b></p>
<p class="MsoNormal" style="text-align:center; background:white" align="center"><b style=""><span style="font-size:14.0pt; line-height:115%" lang="EN">(December 07, 2020, virtual workshop)</span></b></p>
<p class="MsoNormal" style="text-align:center; background:white" align="center"><span lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="text-align:center; background:white" align="center"><b style=""><span lang="EN">Call for Participation</span></b></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="text-align:justify; background:white"><span lang="EN">Despite the impact of the pandemic, the 7th iDASH Secure Genome Analysis Competition and Workshop is now calling for participation from the academia and the industry to showcase
state-of-the-art privacy technologies for protecting real-world biomedical data analysis.<span style="">
</span>In the past 6 years, the iDASH competition has been serving as a bridge between the privacy/security research and biomedical research, challenging the security community to come up with the best solutions that can offer practical supports for privacy-preserving
biomedical computing. It has been widely considered to be a benchmark for evaluating data privacy technologies, particularly when they are applied to biomedical data analysis, and a key source for the biomedical and genomics researchers to seek usable solutions
for protecting their data and computing tasks. This year’s competition is characterized by 3 tracks as described below.</span></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><b style=""><span lang="EN">Competition Tasks</span></b></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><u><span lang="EN">Track 1: Secure multi-label Tumor classification using Homomorphic Encryption</span></u></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">The competitors are required to develop homomorphic encryption (HE) based method for classifying encrypted genetic variant data from tumor samples of unknown type and origin into multiple labels.</span></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><u><span lang="EN">Track 2: Privacy-preserving clustering of single-cell transcriptomics data in SGX</span></u></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">The competitors are expected to implement a trained deep learning model for disease prediction under the protection of SGX, Intel’s trusted execution environment, so the model can work on encrypted
genomic data uploaded by the user.</span></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><u><span lang="EN">Track 3: Differentially private federated learning for the cancer prediction model</span></u></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">The competitors are tasked to train a machine learning model on gene expression data for breast tumors, with all the data secretly shared across multiple servers.<span style="">
</span></span></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><b style=""><span lang="EN">Timeline</span></b></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="margin-top:14.0pt; margin-right:0in; margin-bottom:0in; margin-left:.75in; margin-bottom:.0001pt; text-indent:-.25in; background:white">
<span lang="EN">1.</span><span style="font-size:12.0pt; line-height:115%" lang="EN"><span style="">
</span></span><span lang="EN">Competition start (August 16, 2020)</span></p>
<p class="MsoNormal" style="margin-top:14.0pt; margin-right:0in; margin-bottom:0in; margin-left:.75in; margin-bottom:.0001pt; text-indent:-.25in; background:white">
<span lang="EN">2.</span><span style="font-size:12.0pt; line-height:115%" lang="EN"><span style="">
</span></span><span lang="EN">Solution due (October 31, 2020)</span></p>
<p class="MsoNormal" style="margin-top:14.0pt; margin-right:0in; margin-bottom:0in; margin-left:.75in; margin-bottom:.0001pt; text-indent:-.25in; background:white">
<span lang="EN">3.</span><span style="font-size:12.0pt; line-height:115%" lang="EN"><span style="">
</span></span><span lang="EN">Winner announcement (December 1, 2020)</span></p>
<p class="MsoNormal" style="margin-top:14.0pt; margin-right:0in; margin-bottom:0in; margin-left:.75in; margin-bottom:.0001pt; text-indent:-.25in; background:white">
<span lang="EN">4.</span><span style="font-size:12.0pt; line-height:115%" lang="EN"><span style="">
</span></span><span lang="EN">Workshop day (December 7, 2020)</span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:12.0pt; line-height:115%; font-family:"Times New Roman",serif; color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><b style=""><span lang="EN">Evaluation</span></b></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="text-align:justify; background:white"><span lang="EN">The outcomes of the competition will be evaluated by interdisciplinary teams at Indiana University, UC San Diego, and UT Health, based upon the performance of a solution and its
privacy guarantee.</span></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><b style=""><span lang="EN">Organization</span></b></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">General Chairs: </span>
</p>
<p class="MsoNormal" style="background:white"><span lang="EN">Arif Harmanci (UT Health), Miran Kim (UNIST), Xiaoqian Jiang (UT Health)</span></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">Organization Committee:<span style="">
</span></span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">XiaoFeng Wang (IU), Haixu Tang (IU), Xiaoqian Jiang (UT Health), Miran Kim (UNIST),
</span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">Arif Harmanci (UT Health), Tsung-Ting Kuo (UCSD) and Lucila Ohno-Machado (UCSD)</span></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"> </span></p>
<p class="MsoNormal" style="background:white"><b style=""><span lang="EN">Contact</span></b></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span><span lang="EN"></span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">Track 1 (UT Health):
</span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">Arif Harmanci (</span><span style="font-size:12.0pt; line-height:115%; color:#1155CC" lang="EN">Arif.O.Harmanci@uth.tmc.edu</span><span lang="EN">), Miran Kim (<a href="mailto:mirankim618@gmail.com"><span style="color:#1155CC; text-decoration:none">mirankim618@gmail.com</span></a>),<span style="">
</span>Xiaoqiang Jiang (<a href="mailto:Xiaoqian.Jiang@uth.tmc.edu"><span style="font-size:12.0pt; line-height:115%; color:#1155CC; text-decoration:none">Xiaoqian.Jiang@uth.tmc.edu</span></a>)</span></p>
<p class="MsoNormal" style="background:white"><span lang="EN"> </span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">Track 2 & 3 (IU): </span>
</p>
<p class="MsoNormal" style="background:white"><span lang="EN">Haixu Tang (</span><span style="font-size:12.0pt; line-height:115%; color:#1155CC" lang="EN">hatang@indiana.edu</span><span lang="EN">),<span style="">
</span>XiaoFeng Wang (</span><span style="font-size:12.0pt; line-height:115%; color:#1155CC" lang="EN">xw7@indiana.edu</span><span lang="EN">)</span></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121" lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">Best,</span></p>
<p class="MsoNormal" style="background:white"><span lang="EN"><span style=""> </span></span></p>
<p class="MsoNormal" style="background:white"><span lang="EN">2020 iDASH Privacy & Security Workshop organizers</span></p>
<p class="MsoNormal"><span lang="EN"> </span></p>
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