{"id":4432,"date":"2018-03-01T03:11:11","date_gmt":"2018-03-01T03:11:11","guid":{"rendered":"http:\/\/www.cytognomix.com\/?p=4432"},"modified":"2018-03-01T03:12:17","modified_gmt":"2018-03-01T03:12:17","slug":"february-28-2018-new-publication-on-radiation-biodosimetry-based-upon-machine-learning","status":"publish","type":"post","link":"https:\/\/www.cytognomix.com\/?p=4432","title":{"rendered":"February 28, 2018. New publication on radiation biodosimetry based upon machine learning"},"content":{"rendered":"<h3>We have published a new approach to devise gene signatures to detect radiation exposure (human, murine), and to quantify levels of exposure (murine):<\/h3>\n<blockquote><p><span style=\"font-size: 1.17em;\">Zhao JZL, Mucaki EJ and Rogan PK. Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning.\u00a0<\/span><a title=\"Zhao et al.\" href=\"https:\/\/f1000research.com\/articles\/7-233\/v1\" target=\"_blank\"><i style=\"font-size: 1.17em;\">F1000Research<\/i><\/a><span style=\"font-size: 1.17em;\"><a title=\"Zhao et al.\" href=\"https:\/\/f1000research.com\/articles\/7-233\/v1\" target=\"_blank\">\u00a02018,\u00a07:233<\/a> (doi:\u00a0<\/span><a style=\"font-size: 1.17em;\" href=\"http:\/\/dx.doi.org\/10.12688\/f1000research.14048.1\" target=\"_blank\">10.12688\/f1000research.14048.1<\/a><span style=\"font-size: 1.17em;\">)<\/span><\/p><\/blockquote>\n<p><a href=\"http:\/\/www.cytognomix.com\/wp-content\/uploads\/2018\/03\/Capture.png\"><img loading=\"lazy\" class=\"alignleft size-full wp-image-4433\" alt=\"Capture\" src=\"http:\/\/www.cytognomix.com\/wp-content\/uploads\/2018\/03\/Capture.png\" width=\"660\" height=\"330\" srcset=\"https:\/\/www.cytognomix.com\/wp-content\/uploads\/2018\/03\/Capture.png 1321w, https:\/\/www.cytognomix.com\/wp-content\/uploads\/2018\/03\/Capture-300x150.png 300w, https:\/\/www.cytognomix.com\/wp-content\/uploads\/2018\/03\/Capture-1024x512.png 1024w, https:\/\/www.cytognomix.com\/wp-content\/uploads\/2018\/03\/Capture-900x450.png 900w\" sizes=\"(max-width: 660px) 100vw, 660px\" \/><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We have published a new approach to devise gene signatures to detect radiation exposure (human, murine), and to quantify levels of exposure (murine): Zhao JZL, Mucaki EJ and Rogan PK. Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning.\u00a0F1000Research\u00a02018,\u00a07:233 (doi:\u00a010.12688\/f1000research.14048.1)<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[6],"tags":[],"_links":{"self":[{"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=\/wp\/v2\/posts\/4432"}],"collection":[{"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4432"}],"version-history":[{"count":3,"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=\/wp\/v2\/posts\/4432\/revisions"}],"predecessor-version":[{"id":4436,"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=\/wp\/v2\/posts\/4432\/revisions\/4436"}],"wp:attachment":[{"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4432"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4432"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cytognomix.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4432"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}