{"id":4091,"date":"2012-10-31T14:21:15","date_gmt":"2012-10-31T19:21:15","guid":{"rendered":"https:\/\/www.bu.edu\/bioinformatics\/?p=4091"},"modified":"2012-11-05T15:20:15","modified_gmt":"2012-11-05T20:20:15","slug":"student-seminar-jonathan-dreyfuss","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/bioinformatics\/2012\/10\/31\/student-seminar-jonathan-dreyfuss\/","title":{"rendered":"Student Seminar: Jonathan Dreyfuss"},"content":{"rendered":"<p><strong>Speaker: <\/strong> Jonathan Dreyfuss<br \/>\n<strong>Adviser: <\/strong> James Galagan<br \/>\n<strong>Title: <\/strong> Genome-scale metabolic reconstruction and validation of the filamentous fungus Neurospora crassa<\/p>\n<p><strong>ABTRACT<\/strong><br \/>\nStudies of the model organism Neurospora crassa have laid the foundation for genetics, biochemistry, and molecular biology over the past century. Despite this rich history, no one has systematically integrated the detailed knowledge of its metabolism to accurately predict growth phenotype from its genotype. Based on an extensively curated knowledge base (NeurosporaCyc) and a novel optimization-based method called Fast Automated Reconstruction of Metabolism (FARM), we trained a genome-scale model of Neurospora using a curated list of gene knockout and supplemental rescue phenotypes until our predictions were highly consistent with experiment.  We then validated the predictive power of our model with an independent test set, achieving &gt;93% specificity and sensitivity. I will discuss the status of the project and the methods I developed, which may be useful to others involved in metabolic flux analysis.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Speaker: Jonathan Dreyfuss Adviser: James Galagan Title: Genome-scale metabolic reconstruction and validation of the filamentous fungus Neurospora crassa ABTRACT Studies of the model organism Neurospora crassa have laid the foundation for genetics, biochemistry, and molecular biology over the past century. Despite this rich history, no one has systematically integrated the detailed knowledge of its metabolism [&hellip;]<\/p>\n","protected":false},"author":1391,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[376],"tags":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/posts\/4091"}],"collection":[{"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/users\/1391"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/comments?post=4091"}],"version-history":[{"count":3,"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/posts\/4091\/revisions"}],"predecessor-version":[{"id":4108,"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/posts\/4091\/revisions\/4108"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/media?parent=4091"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/categories?post=4091"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/bioinformatics\/wp-json\/wp\/v2\/tags?post=4091"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}