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Genome informatics of influenza A: from data sharing to shared analytical capabilities

Published online by Cambridge University Press:  01 July 2010

Daniel A. Janies ,
Igor O. Voronkin ,
Manirupa Das ,
Jori Hardman ,
Travis W. Treseder  and
Jonathon Studer
Daniel A. Janies*
Affiliation:
Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
Igor O. Voronkin
Affiliation:
Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
Manirupa Das
Affiliation:
Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
Jori Hardman
Affiliation:
Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
Travis W. Treseder
Affiliation:
Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
Jonathon Studer
Affiliation:
Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
*
*Corresponding author. E-mail: [email protected]
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Abstract

Emerging infectious diseases are critical issues of public health and the economic and social stability of nations. As demonstrated by the international response to the severe acute respiratory syndrome (SARS) and influenza A, rapid genomic sequencing is a crucial tool to understand diseases that occur at the interface of human and animal populations. However, our ability to make sense of sequence data lags behind our ability to acquire the data. The potential of sequence data on pathogens is not fully realized until raw data are translated into public health intelligence. Sequencing technologies have become highly mechanized. If the political will for data sharing remains strong, the frontier for progress in emerging infectious diseases will be in analysis of sequence data and translation of results into better public health science and policy. For example, applying analytical tools such as Supramap (http://supramap.osu.edu) to genomic data for pathogens, public health scientists can track specific mutations in pathogens that confer the ability to infect humans or resist drugs. The results produced by the Supramap application are compelling visualizations of pathogen lineages and features mapped into geographic information systems that can be used to test hypotheses and to follow the spread of diseases across geography and hosts and communicate the results to a wide audience.

Keywords

genomicsinformaticspathogensphylogeneticsdata sharingGISAIDGenBankSupramapinfluenza Aepidemiologyevolutionpublic health
Type
Review Article
Information
Animal Health Research Reviews , Volume 11 , Issue 1: Influenza in Animals , June 2010 , pp. 73 - 79
Copyright
Copyright © Cambridge University Press 2010

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