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www.fludb.org Bioinformatics Resource Centers Influenza Research Database (IRD) Virus Pathogen Database and Analysis Resource (ViPR) 8 December 2010 Richard H. Scheuermann, Ph.D. Department of Pathology U.T. Southwestern Medical Center
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www.fludb.org NIAID Scientific Resources http://www.niaid.nih.gov/labsandresources/resources/Pages/default.aspx
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www.fludb.org DMID Resources List
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www.fludb.org DMID BRC Resources
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www.fludb.org Category A Pathogens
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www.fludb.org Category B Pathogens
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www.fludb.org Category A Pathogens
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www.fludb.org DMID BRC Resources
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www.fludb.org BRC Portal
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www.fludb.org ViPR www.viprbrc.org
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www.fludb.org Influenza Research Database (IRD) www.fludb.org
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IRD Home Page
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www.fludb.org Public Health Impact of Influenza Seasonal flu epidemics occur yearly during the fall/ winter months and result in 3-5 million cases of severe illness worldwide. More than 200,000 people are hospitalized each year with seasonal flu-related complications in the U.S. Approximately 36,000 deaths occur due to seasonal flu each year in the U.S. Populations at highest risk are children under age 2, adults age 65 and older, and groups with other comorbidities. Source: World Health Organization - http://www.who.int/mediacentre/factsheets/fs211/en/index.html
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www.fludb.org Known flu pandemics occurring during the 20 th and 21 st centuries 1) 1918 flu pandemic (Spanish flu) - Subtype H1N1 - the most severe pandemic - estimated to have claimed between 2.5% to 5.0% of the world’s population (20 > 100 million deaths) 2) Asian flu (1957 - 1958) - Subtype H2N2 - 1 > 1.5 million deaths 3) Hong Kong flu (1968 - 1969) - Subtype H3N2 - between 750,000 and 1 million deaths 4) 2009 H1N1 - Subtype H1N1 - > 16,000 deaths as of March 2010
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www.fludb.org Influenza Virus Orthomyxoviridae family Negative-strand RNA Segmented Enveloped 8 RNA segments encode 11 proteins Classified based on serology of HA and NA
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www.fludb.org IRD Overview www.fludb.org
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Data - sequence IRD Data
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www.fludb.org Data - surveillance IRD Data
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www.fludb.org Surveillance detail page Implicit versus explicit semantics
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www.fludb.org Strain detail page
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www.fludb.org Segment detail page 1
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www.fludb.org Segment detail page 2
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www.fludb.org Segment search taxonomygazeteer
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www.fludb.org Data – 3D protein structure IRD Data
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www.fludb.org 3D protein structure search results
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www.fludb.org 3D Structures & Integration Visualize protein structure in 3D Display sequence conservation heat map on the structure Highlight sequence features (epitopes, etc.) Download highlighted protein structure image
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www.fludb.org 3D Structure
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www.fludb.org Analysis and Visualization Tools
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www.fludb.org My Workbench
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www.fludb.org IRD IRD Summary Funded by U.S. National Institute of Allergy and Infectious Diseases (NIAID) Free and open access with no use restrictions Developed by a team of research scientists, bioinformaticians and professional software developers Comprehensive collection of public data Novel derived data, novel analytical tools, unique functions Integration – Integration – Integration www.fludb.org
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31 U.T. Southwestern – Richard Scheuermann – Burke Squires – Jyothi Noronha – Victoria Hunt – Shubhada Godbole – Brett Pickett – Mengya Liu MSSM – Adolfo Garcia-Sastre – Eric Bortz – Gina Conenello – Peter Palese Vecna – Chris Larsen – Al Ramsey LANL – Catherine Macken – Mira Dimitrijevic U.C. Davis – Nicole Baumgarth Northrop Grumman – Ed Klem – Mike Atassi – Kevin Biersack – Jon Dietrich – Wenjie Hua – Wei Jen – Sanjeev Kumar – Xiaomei Li – Zaigang Liu – Jason Lucas – Michelle Lu – Bruce Quesenberry – Barbara Rotchford – Hongbo Su – Bryan Walters – Jianjun Wang – Sam Zaremba – Liwei Zhou IRD SWG – Gillian Air, OMRF – Carol Cardona, Univ. Minnesota – Adolfo Garcia-Sastre, Mt Sinai – Elodie Ghedin, Univ. Pittsburgh – Martha Nelson, Fogarty – Daniel Perez, Univ. Maryland – Gavin Smith, Duke Singapore – David Spiro, JCVI – Dave Stallknecht, Univ. Georgia – David Topham, Rochester – Richard Webby, St Jude USDA – David Suarez Sage Analytica – Robert Taylor – Lone Simonsen CEIRS Centers Acknowledgements
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www.fludb.org SFVT approach VT-1I F D R L E T L I L VT-2I F N R L E T L I L VT-3I F D R L E T I V L VT-4L F D Q L E T L V S VT-5I F D R L E N L T L VT-6I F N R L E A L I L VT-7I Y D R L E T L I L VT-8I F D R L E T L V L VT-9I F D R L E N I V L VT-10I F E R L E T L I L VT-11 L F D Q M E T L V S Influenza A_NS1_nuclear-export-signal_137(10) Identify regions of protein/gene with known structural or functional properties – Sequence Features (SF) an alpha-helical region, the binding site for another protein, an enzyme active site, an immune epitope Determine the extent of sequence variation for each SF by defining each unique sequence as a Variant Type (VT) High-level, comprehensive grouping of all virus strains by VT membership for each SF independently Influenza A_NS1_alpha-helix_171(17)
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