<HashMap><database>biostudies-literature</database><scores/><additional><submitter>AlShaikhahmed K</submitter><funding>US National Institutes of Health</funding><funding>NIAID NIH HHS</funding><funding>Peter Stockley, University of Leeds</funding><funding>EPSRC</funding><funding>Wellcome Trust</funding><funding>Biotechnology and Biological Sciences Research Council</funding><funding>Engineering and Physical Sciences Research Council</funding><pagination>12087-12098</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6294558</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>46(22)</volume><pubmed_abstract>Viruses with segmented genomes, including pathogens such as influenza virus, Rotavirus and Bluetongue virus (BTV), face the collective challenge of packaging their genetic material in terms of the correct number and types of segments. Here we develop a novel network approach to predict RNA-RNA interactions between different genomic segments. Experimental data on RNA complex formation in the multi-segmented BTV genome are used to establish proof-of-concept of this technique. In particular, we show that trans interactions between segments occur at multiple specific sites, termed segment assortment signals (SASs) that are dispersed across each segment. In order to validate the putative trans acting networks, we used various biochemical and molecular techniques which confirmed predictions of t</pubmed_abstract><journal>Nucleic acids research</journal><pubmed_title>Dynamic network approach for the modelling of genomic sub-complexes in multi-segmented viruses.</pubmed_title><pmcid>PMC6294558</pmcid><funding_grant_id>100218</funding_grant_id><funding_grant_id>110145/Z/15/Z</funding_grant_id><funding_grant_id>R01 AI045000</funding_grant_id><funding_grant_id>BB/P00542X/1</funding_grant_id><funding_grant_id>110145</funding_grant_id><funding_grant_id>BB/P00542X</funding_grant_id><funding_grant_id>110146</funding_grant_id><funding_grant_id>BB/J014877/1</funding_grant_id><funding_grant_id>EP/R023204/1</funding_grant_id><funding_grant_id>R01AI045000</funding_grant_id><pubmed_authors>Bingham RJ</pubmed_authors><pubmed_authors>AlShaikhahmed K</pubmed_authors><pubmed_authors>Sung PY</pubmed_authors><pubmed_authors>Twarock R</pubmed_authors><pubmed_authors>Roy P</pubmed_authors><pubmed_authors>Leonov G</pubmed_authors></additional><is_claimable>false</is_claimable><name>Dynamic network approach for the modelling of genomic sub-complexes in multi-segmented viruses.</name><description>Viruses with segmented genomes, including pathogens such as influenza virus, Rotavirus and Bluetongue virus (BTV), face the collective challenge of packaging their genetic material in terms of the correct number and types of segments. Here we develop a novel network approach to predict RNA-RNA interactions between different genomic segments. Experimental data on RNA complex formation in the multi-segmented BTV genome are used to establish proof-of-concept of this technique. In particular, we show that trans interactions between segments occur at multiple specific sites, termed segment assortment signals (SASs) that are dispersed across each segment. In order to validate the putative trans acting networks, we used various biochemical and molecular techniques which confirmed predictions of t</description><dates><release>2018-01-01T00:00:00Z</release><publication>2018 Dec</publication><modification>2026-07-09T12:08:51.748Z</modification><creation>2019-03-27T00:13:15Z</creation></dates><accession>S-EPMC6294558</accession><cross_references><pubmed>30299495</pubmed><doi>10.1093/nar/gky881</doi></cross_references></HashMap>