{"id":2793,"date":"2023-06-13T01:08:23","date_gmt":"2023-06-13T00:08:23","guid":{"rendered":"https:\/\/archive.belbi.bg.ac.rs\/2023\/?post_type=abstract&#038;p=2793"},"modified":"2023-06-14T18:37:24","modified_gmt":"2023-06-14T17:37:24","slug":"deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet","status":"publish","type":"abstract","link":"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/","title":{"rendered":"Deciphering key regulatory networks and drug repurposing candidates through scRNAseq data analysis using SCANet"},"content":{"rendered":"\n<p>Mhaned Oubounyt<sup>1*<\/sup>, Jan Baumbach<sup>1<\/sup>, and Maria L. Elkjaer<sup>1<\/sup><\/p>\n\n\n\n<p class=\"affiliation-para\"><sup>1<\/sup> Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany<\/p>\n\n\n\n<p>mhaned.oubounyt [at] uni-hamburg.de<\/p>\n\n\n\n<p><strong>Abstract<\/strong><\/p>\n\n\n\n<p class=\"abstract-para\">Differences in co-expression networks between two or multiple cell (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and\/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN and GRN pipeline including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. To illustrate the power of SCANet, we examined data from two studies. First, we identify the drivers of the mechanotype of a cytokine storm associated with increased mortality in patients with acute respiratory illness. Secondly, we find 20 drugs for 8 potential pharmacological targets in cellular driver mechanisms in the intestinal stem cells of obese mice. SCANet is available as a free, open source, and user-friendly Python package that can be easily integrated in systems biology pipelines.<\/p>\n\n\n\n<p class=\"abstract-para\"><strong>Keywords:<\/strong> small single cell networks, GRN, GCN, mechanotyping, drug repurposing<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Mhaned Oubounyt<sup>1*<\/sup>, Jan Baumbach<sup>1<\/sup>, and Maria L. Elkjaer<sup>1<\/sup><\/p>\n<p class=\"affiliation-para\"><sup>1<\/sup> Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":162,"featured_media":0,"template":"","categories":[18],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Deciphering key regulatory networks and drug repurposing candidates through scRNAseq data analysis using SCANet - BelBi 2023<\/title>\n<meta name=\"robots\" content=\"noindex, follow\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Deciphering key regulatory networks and drug repurposing candidates through scRNAseq data analysis using SCANet - BelBi 2023\" \/>\n<meta property=\"og:description\" content=\"Mhaned Oubounyt1*, Jan Baumbach1, and Maria L. Elkjaer11 Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany Continue reading\" \/>\n<meta property=\"og:url\" content=\"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/\" \/>\n<meta property=\"og:site_name\" content=\"BelBi 2023\" \/>\n<meta property=\"article:modified_time\" content=\"2023-06-14T17:37:24+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/\",\"url\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/\",\"name\":\"Deciphering key regulatory networks and drug repurposing candidates through scRNAseq data analysis using SCANet - BelBi 2023\",\"isPartOf\":{\"@id\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/#website\"},\"datePublished\":\"2023-06-13T00:08:23+00:00\",\"dateModified\":\"2023-06-14T17:37:24+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Deciphering key regulatory networks and drug repurposing candidates through scRNAseq data analysis using SCANet\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/#website\",\"url\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/\",\"name\":\"BelBi 2023\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/#organization\",\"name\":\"Belgrade Bioinformatics Conference\",\"url\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-content\/uploads\/2023\/02\/145_97_171.png\",\"contentUrl\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-content\/uploads\/2023\/02\/145_97_171.png\",\"width\":278,\"height\":500,\"caption\":\"Belgrade Bioinformatics Conference\"},\"image\":{\"@id\":\"https:\/\/archive.belbi.bg.ac.rs\/2023\/#\/schema\/logo\/image\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Deciphering key regulatory networks and drug repurposing candidates through scRNAseq data analysis using SCANet - BelBi 2023","robots":{"index":"noindex","follow":"follow"},"og_locale":"en_US","og_type":"article","og_title":"Deciphering key regulatory networks and drug repurposing candidates through scRNAseq data analysis using SCANet - BelBi 2023","og_description":"Mhaned Oubounyt1*, Jan Baumbach1, and Maria L. Elkjaer11 Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany Continue reading","og_url":"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/","og_site_name":"BelBi 2023","article_modified_time":"2023-06-14T17:37:24+00:00","twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/","url":"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/","name":"Deciphering key regulatory networks and drug repurposing candidates through scRNAseq data analysis using SCANet - BelBi 2023","isPartOf":{"@id":"https:\/\/archive.belbi.bg.ac.rs\/2023\/#website"},"datePublished":"2023-06-13T00:08:23+00:00","dateModified":"2023-06-14T17:37:24+00:00","breadcrumb":{"@id":"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/archive.belbi.bg.ac.rs\/2023\/abstract\/deciphering-key-regulatory-networks-and-drug-repurposing-candidates-through-scrnaseq-data-analysis-using-scanet\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/archive.belbi.bg.ac.rs\/2023\/"},{"@type":"ListItem","position":2,"name":"Deciphering key regulatory networks and drug repurposing candidates through scRNAseq data analysis using SCANet"}]},{"@type":"WebSite","@id":"https:\/\/archive.belbi.bg.ac.rs\/2023\/#website","url":"https:\/\/archive.belbi.bg.ac.rs\/2023\/","name":"BelBi 2023","description":"","publisher":{"@id":"https:\/\/archive.belbi.bg.ac.rs\/2023\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/archive.belbi.bg.ac.rs\/2023\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/archive.belbi.bg.ac.rs\/2023\/#organization","name":"Belgrade Bioinformatics Conference","url":"https:\/\/archive.belbi.bg.ac.rs\/2023\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/archive.belbi.bg.ac.rs\/2023\/#\/schema\/logo\/image\/","url":"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-content\/uploads\/2023\/02\/145_97_171.png","contentUrl":"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-content\/uploads\/2023\/02\/145_97_171.png","width":278,"height":500,"caption":"Belgrade Bioinformatics Conference"},"image":{"@id":"https:\/\/archive.belbi.bg.ac.rs\/2023\/#\/schema\/logo\/image\/"}}]}},"_links":{"self":[{"href":"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-json\/wp\/v2\/abstract\/2793"}],"collection":[{"href":"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-json\/wp\/v2\/abstract"}],"about":[{"href":"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-json\/wp\/v2\/types\/abstract"}],"author":[{"embeddable":true,"href":"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-json\/wp\/v2\/users\/162"}],"wp:attachment":[{"href":"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-json\/wp\/v2\/media?parent=2793"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-json\/wp\/v2\/categories?post=2793"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/archive.belbi.bg.ac.rs\/2023\/wp-json\/wp\/v2\/tags?post=2793"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}