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A Crowdsourced Analysis to Identify Ab Initio Molecular Signatures Predictive of Susceptibility to Viral Infection
Nature Communications
  • Slim Fourati
  • Aarthi Talla
  • Mehrad Mahmoudian
  • Joshua G. Burkhart
  • Riku Klén
  • Ricardo Henao
  • Thomas Yu
  • Zafer Aydın
  • Ka Yee Yeung, University of Washington Tacoma
  • Mehmet Eren Ahsen
  • Reem Almugbel
  • Samad Jahandideh
  • Xiao Liang
  • Torbjörn E. Nordling
  • Motoki Shiga
  • Ana Stanescu
  • Robert Vogel
  • Gaurav Pandey
  • Christopher Chiu
  • Micah T. McClain
  • Christopher W. Woods
  • Geoffrey S. Ginsburg
  • Laura L. Elo
  • Ephraim L. Tsalik
  • Lara M. Mangravite
  • Solveig K. Sieberts
Publication Date
10-24-2018
Document Type
Article
Abstract

The response to respiratory virus exposure can currently not be predicted by pre- or early post-exposure molecular signatures. Here, the authors conduct a community-based analysis of blood gene expression from healthy individuals exposed to respiratory viruses and provide predictive models and biological insight into the physiological response.

DOI
10.1038/s41467-018-06735-8
Version
open access
Citation Information
Slim Fourati, Aarthi Talla, Mehrad Mahmoudian, Joshua G. Burkhart, et al.. "A Crowdsourced Analysis to Identify Ab Initio Molecular Signatures Predictive of Susceptibility to Viral Infection" Nature Communications Vol. 9 Iss. 1 (2018)
Available at: http://works.bepress.com/ky-yeung/5/