{"id":377,"date":"2021-10-01T15:10:00","date_gmt":"2021-10-01T22:10:00","guid":{"rendered":"https:\/\/dornsife.usc.edu\/research-briefs\/?p=377"},"modified":"2023-05-01T15:19:48","modified_gmt":"2023-05-01T22:19:48","slug":"deep-learning-inference-using-knockoffs","status":"publish","type":"post","link":"https:\/\/dornsife.usc.edu\/news-briefs\/natural-sciences\/2021\/10\/deep-learning-inference-using-knockoffs\/","title":{"rendered":"Deep Learning Inference Using Knockoffs"},"content":{"rendered":"\n\n  \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--rich-text \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--rich-text\"\n    \n      >\n\n    \n      \n<div class=\"f--field f--wysiwyg\">\n\n    \n  <h2>Deep Learning Inference Using Knockoffs<\/h2>\n<p><strong>Oct. 1, 2021 | Fengzhu Sun, professor of quantitative and computational biology and mathematics<\/strong><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-378\" src=\"https:\/\/dornsife.usc.edu\/research-briefs\/wp-content\/uploads\/sites\/182\/2023\/04\/QBIO.jpg\" alt=\"Round portraits of five people.\" width=\"800\" height=\"520\" srcset=\"https:\/\/dornsife.usc.edu\/news-briefs\/wp-content\/uploads\/sites\/182\/2023\/04\/QBIO.jpg 800w, https:\/\/dornsife.usc.edu\/news-briefs\/wp-content\/uploads\/sites\/182\/2023\/04\/QBIO-300x195.jpg 300w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><\/p>\n<p>New technologies generate enormous amounts of data, such as genetic polymorphisms, gene expression or microbiome. These studies usually generate thousands to hundreds of thousands of variables (features) such as abundance levels of microbial organisms or expression levels of genes. To link these features to public health is a highly important problem.<\/p>\n<p>Machine learning, and particularly deep learning, has been successfully used to predict health outcomes. However, selecting variables truly associated with the health status with controlled false discovery rates is an unsolved problem.<\/p>\n<p>In our paper, \u201c<a href=\"https:\/\/www.pnas.org\/content\/118\/36\/e2104683118\" target=\"_blank\" rel=\"noopener\">DeepLINK: Deep learning inference using knockoffs with applications to genomics<\/a>,\u201d published in the\u00a0<i>Proceedings of the National Academy of Sciences<\/i>, we developed a method to select features from high dimensional data using deep learning. Study authors include myself, Ph.D. student Zifan Zhu; Yingying Fan, professor of data sciences and operations, and Jinchi Lv, Kenneth King Stonier Chair in Business Administration and professor of data sciences and operations, both at USC Marshall School of Business; and Yinfei Kong, associate professor of information systems and decision sciences at California State University, Fullertion.<\/p>\n<p>Our USC Dornsife group, together with Jed Fuhrman, McCulloch-Crosby Chair in Marine Biology and professor of biological sciences, and Emily Zakem, Simons Foundation Postdoctoral Fellow in marine and environmental biology, Yan Liu, professor of computer science at the USC Viterbi School of Engineering, and Dr. Lv received a National Science Foundation\u00a0<a href=\"https:\/\/www.nsf.gov\/news\/special_reports\/big_ideas\/life.jsp\" target=\"_blank\" rel=\"noopener\">Understanding the Rules of Life<\/a>\u00a0$2.5 million grant to study microbial interactions in marine environments.<\/p>\n<p>It is also great to know that Eric Webb, associate professor of biological sciences and environmental studies, et. al. also received a grant from the same program. This is probably quite unique for two groups from the same university.<\/p>\n\n\n\n<\/div>\n\n\n  <\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>With the reconciliation package stalled in Washington, D.C., progressive champions have lamented their failure to capture the public imagination and secure support for a social safety net that fits our 21st-century economy. This is not a new issue. Progressives have often faced difficulties articulating their agenda, frequently getting caught in a game of telephone in which their plans for full inclusion get garbled into pleas for \u201cspecial interests\u201d and a laundry list of specific policies.<\/p>\n","protected":false},"author":13,"featured_media":378,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[13,11],"tags":[],"class_list":["post-377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-natural-sciences","category-research-brief"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Deep Learning Inference Using Knockoffs<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dornsife.usc.edu\/news-briefs\/natural-sciences\/2021\/10\/deep-learning-inference-using-knockoffs\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Deep Learning Inference Using Knockoffs - USC Dornsife News Briefs\" \/>\n<meta property=\"og:description\" content=\"With the reconciliation package stalled in Washington, D.C., progressive champions have lamented their failure to capture the public imagination and secure support for a social safety net that fits our 21st-century economy. This is not a new issue. Progressives have often faced difficulties articulating their agenda, frequently getting caught in a game of telephone in which their plans for full inclusion get garbled into pleas for \u201cspecial interests\u201d and a laundry list of specific policies.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dornsife.usc.edu\/news-briefs\/natural-sciences\/2021\/10\/deep-learning-inference-using-knockoffs\/\" \/>\n<meta property=\"og:site_name\" content=\"USC Dornsife News Briefs\" \/>\n<meta property=\"article:published_time\" content=\"2021-10-01T22:10:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-05-01T22:19:48+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dornsife.usc.edu\/news-briefs\/wp-content\/uploads\/sites\/182\/2023\/04\/QBIO.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"800\" \/>\n\t<meta property=\"og:image:height\" content=\"520\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Michael Liu\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/dornsife.usc.edu\/news-briefs\/natural-sciences\/2021\/10\/deep-learning-inference-using-knockoffs\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/dornsife.usc.edu\/news-briefs\/natural-sciences\/2021\/10\/deep-learning-inference-using-knockoffs\/\"},\"author\":{\"name\":\"Michael Liu\",\"@id\":\"https:\/\/dornsife.usc.edu\/news-briefs\/#\/schema\/person\/d03084ed5319ed7575c96017879a7447\"},\"headline\":\"Deep Learning Inference Using Knockoffs\",\"datePublished\":\"2021-10-01T22:10:00+00:00\",\"dateModified\":\"2023-05-01T22:19:48+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/dornsife.usc.edu\/news-briefs\/natural-sciences\/2021\/10\/deep-learning-inference-using-knockoffs\/\"},\"wordCount\":5,\"image\":{\"@id\":\"https:\/\/dornsife.usc.edu\/news-briefs\/natural-sciences\/2021\/10\/deep-learning-inference-using-knockoffs\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/dornsife.usc.edu\/news-briefs\/wp-content\/uploads\/sites\/182\/2023\/04\/QBIO.jpg\",\"articleSection\":[\"Natural Sciences\",\"Research Brief\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/dornsife.usc.edu\/news-briefs\/natural-sciences\/2021\/10\/deep-learning-inference-using-knockoffs\/\",\"url\":\"https:\/\/dornsife.usc.edu\/news-briefs\/natural-sciences\/2021\/10\/deep-learning-inference-using-knockoffs\/\",\"name\":\"Deep Learning Inference Using Knockoffs - 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