Title
A Crowdsourced Analysis to Identify Ab Initio Molecular Signatures Predictive of Susceptibility to Viral Infection
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.
Publication Title
Nature Communications
Volume
9
Issue
1
DOI
10.1038/s41467-018-06735-8
Publisher Policy
open access
Open Access Status
OA Journal
Recommended Citation
Fourati, Slim; Talla, Aarthi; Mahmoudian, Mehrad; Burkhart, Joshua G.; Klén, Riku; Henao, Ricardo; Yu, Thomas; Aydın, Zafer; Yeung, Ka Yee; Ahsen, Mehmet Eren; Almugbel, Reem; Jahandideh, Samad; Liang, Xiao; Nordling, Torbjörn E.; Shiga, Motoki; Stanescu, Ana; Vogel, Robert; Pandey, Gaurav; Chiu, Christopher; McClain, Micah T.; Woods, Christopher W.; Ginsburg, Geoffrey S.; Elo, Laura L.; Tsalik, Ephraim L.; Mangravite, Lara M.; and Sieberts, Solveig K., "A Crowdsourced Analysis to Identify Ab Initio Molecular Signatures Predictive of Susceptibility to Viral Infection" (2018). School of Engineering and Technology Publications. 272.
https://digitalcommons.tacoma.uw.edu/tech_pub/272
