{"id":237,"date":"2014-11-07T01:26:24","date_gmt":"2014-11-07T01:26:24","guid":{"rendered":"http:\/\/blogs.discovery.wisc.edu\/compsysbio\/?p=237"},"modified":"2014-11-07T01:26:24","modified_gmt":"2014-11-07T01:26:24","slug":"predicting-spatio-temporal-patterns-of-expression","status":"publish","type":"post","link":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/2014\/11\/07\/predicting-spatio-temporal-patterns-of-expression\/","title":{"rendered":"Predicting spatio-temporal patterns of expression"},"content":{"rendered":"<p>An open question in gene regulation is how spatio-temporal patterns of gene expression is encoded in the genome. We discussed <a title=\"this paper\" href=\"http:\/\/www.ploscompbiol.org\/article\/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002798#abstract0\">this paper<\/a>\u00a0in our lab meeting. This paper talks about \u00a0a two-step approach to predicting spatial \u00a0and temporal gene expression patterns in Drosophila. This prediction task is tackled as a two-step approach: (a) first find cis-regulatory modules that exhibit spatio or temporal activity, (b) second link the crms to predict spatio-temporal expression. Assume space and time is captured by the term &#8220;context&#8221;. \u00a0To do (a) the authors use a Bayesian network which is trained on known CRM-context relationships. To do (b) the authors use additional data based on insulators and H3K4me1 to predict which CRMs are associated with which genes. In (a) the CRM-context information is known only for a few hundred of the total 8000 crms that are present. So the authors use an EM idea where they use the trained Bayesian network to predict the context-specific activity of each CRM. Then using the soft labels of each CRM they predict the expression of the gene. This second model is also a Bayesian network but has additional variables for the distance between CRMs and genes and whether there is an insulator binding site.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>An open question in gene regulation is how spatio-temporal patterns of gene expression is encoded in the genome. We discussed this paper\u00a0in our lab meeting. This paper talks about \u00a0a two-step approach to predicting spatial \u00a0and temporal gene expression patterns &hellip; <a href=\"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/2014\/11\/07\/predicting-spatio-temporal-patterns-of-expression\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[10,18],"tags":[],"_links":{"self":[{"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/posts\/237"}],"collection":[{"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/comments?post=237"}],"version-history":[{"count":3,"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/posts\/237\/revisions"}],"predecessor-version":[{"id":241,"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/posts\/237\/revisions\/241"}],"wp:attachment":[{"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/media?parent=237"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/categories?post=237"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.discovery.wisc.edu\/compsysbio\/wp-json\/wp\/v2\/tags?post=237"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}