{"id":2687,"date":"2017-12-03T19:22:01","date_gmt":"2017-12-03T19:22:01","guid":{"rendered":"https:\/\/daslab-tmp.su.domains\/?p=2687"},"modified":"2024-07-30T19:56:31","modified_gmt":"2024-07-30T19:56:31","slug":"were-pleased-to-report-our-latest-methods-in-3d-rna-modeling-and-eterna-design-three-preprints-on-biorxiv-highlight-blind-prediction-of-noncanonical-rna-structure-at-atomic-accuracy-computational","status":"publish","type":"post","link":"https:\/\/daslab-tmp.su.domains\/?p=2687","title":{"rendered":"We&#8217;re pleased to report our latest methods in 3D RNA modeling and Eterna design. Three preprints on BioRxiv highlight Blind prediction of noncanonical RNA structure at atomic accuracy, Computational design of asymmetric three-dimensional RNA structures and machines, and Prospects for recurrent neural network models to learn RNA biophysics from high-throughput data. Check out preprints through our publications page"},"content":{"rendered":"<p>We&#8217;re pleased to report our latest methods in 3D RNA modeling and Eterna design. Three preprints on BioRxiv highlight\u00a0<a href=\"https:\/\/doi.org\/10.1101\/223305\" target=\"_blank\" rel=\"noopener\"><b>Blind prediction of noncanonical RNA structure at atomic accuracy<\/b><\/a>,\u00a0<a href=\"https:\/\/doi.org\/10.1101\/223305\" target=\"_blank\" rel=\"noopener\"><b>Computational design of asymmetric three-dimensional RNA structures and machines<\/b><\/a>, and\u00a0<a href=\"https:\/\/doi.org\/10.1101\/227611\" target=\"_blank\" rel=\"noopener\"><b>Prospects for recurrent neural network models to learn RNA biophysics from high-throughput data<\/b><\/a>. Check out preprints through our\u00a0<a href=\"https:\/\/daslab.stanford.edu\/publications\/\" target=\"_blank\" rel=\"noopener\">publications page<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We&#8217;re pleased to report our latest methods in 3D RNA modeling and Eterna design. Three preprints on BioRxiv highlight\u00a0Blind prediction of noncanonical RNA structure at atomic accuracy,\u00a0Computational design of asymmetric three-dimensional RNA structures and machines, and\u00a0Prospects for recurrent neural network models to learn RNA biophysics from high-throughput data. Check out preprints through our\u00a0publications page<\/p>\n","protected":false},"author":1,"featured_media":2773,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[],"class_list":["post-2687","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"_links":{"self":[{"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=\/wp\/v2\/posts\/2687","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2687"}],"version-history":[{"count":0,"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=\/wp\/v2\/posts\/2687\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=\/wp\/v2\/media\/2773"}],"wp:attachment":[{"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2687"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2687"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/daslab-tmp.su.domains\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2687"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}