{"id":6649,"date":"2023-04-02T00:57:05","date_gmt":"2023-04-01T22:57:05","guid":{"rendered":"https:\/\/zbi-dev.cs.uni-saarland.de\/?post_type=event_listing&p=6649"},"modified":"2023-04-06T11:36:53","modified_gmt":"2023-04-06T09:36:53","slug":"talk-by-prof-dr-julien-gagneur","status":"publish","type":"event_listing","link":"https:\/\/zbi-dev.cs.uni-saarland.de\/en\/event\/talk-by-prof-dr-julien-gagneur\/","title":{"rendered":"Talk by Prof. Dr. Julien Gagneur"},"content":{"rendered":"\n

On Wednesday, January 15, 2020, Prof. Dr. Julien Gagneur (Technical University of Munich, TUM Chair of Computer Science, Germany) will give a lecture as part of the ZBI “Distinguished Speaker Series” on “Modeling the regulatory code: From basic biology to clinical research”.<\/p>\n\n\n\n

Abstract<\/h4>\n\n\n\n

My lab is interested in understanding how gene expression is encoded in genomes, and how to leverage this knowledge for medical application. To this end, we employ statistical modeling of \u2018omics data and work in close collaboration with experimentalists. I will provide an overview of recent studies on RNA metabolism [1] and protein expression control [2] and on deep learning based models of cis-regulatory elements [3,4]. I will also report on methodologies for using RNA-sequencing as a powerful companion tool to genome sequencing for pinpointing causes of rare genetic disorders [5,6].<\/p>\n\n\n\n

References <\/h4>\n\n\n\n
    \n
  1. Wachutka et al., Global donor and acceptor splicing site kinetics in human cells, eLife, 2019 <\/li>\n\n\n\n
  2. Eraslan et al., Quantification and discovery of sequence determinants of protein per mRNA amount in 29 human tissues Mol Syst. Biol. 2019 <\/li>\n\n\n\n
  3. Cheng et al. Modular modeling improves the predictions of genetic variant effects on splicing. Genome Biology, 2019 <\/li>\n\n\n\n
  4. Avsec et al. Kipoi: Accelerating the community exchange and reuse of predictive models for genomics. Nature Biotechnology, 2019<\/li>\n\n\n\n
  5. Kremer et al. Genetic diagnosis of Mendelian disorders via RNA sequencing. Nature Communications, 2017 <\/li>\n\n\n\n
  6. Brechtmann et al. OUTRIDER: A Statistical Method for Detecting Aberrantly Expressed Genes in RNA Sequencing Data. AJHG, 2018<\/li>\n<\/ol>\n","protected":false},"featured_media":0,"template":"","meta":[],"event_listing_category":[266],"event_listing_type":[378],"acf":[],"_links":{"self":[{"href":"https:\/\/zbi-dev.cs.uni-saarland.de\/wp-json\/wp\/v2\/event_listing\/6649"}],"collection":[{"href":"https:\/\/zbi-dev.cs.uni-saarland.de\/wp-json\/wp\/v2\/event_listing"}],"about":[{"href":"https:\/\/zbi-dev.cs.uni-saarland.de\/wp-json\/wp\/v2\/types\/event_listing"}],"wp:attachment":[{"href":"https:\/\/zbi-dev.cs.uni-saarland.de\/wp-json\/wp\/v2\/media?parent=6649"}],"wp:term":[{"taxonomy":"event_listing_category","embeddable":true,"href":"https:\/\/zbi-dev.cs.uni-saarland.de\/wp-json\/wp\/v2\/event_listing_category?post=6649"},{"taxonomy":"event_listing_type","embeddable":true,"href":"https:\/\/zbi-dev.cs.uni-saarland.de\/wp-json\/wp\/v2\/event_listing_type?post=6649"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}