Work

Predictive Modeling of Influenza Shows the Promise of Applied Evolutionary Biology

Year: 2017

Type: review

Source: Trends in Microbiology

DOI: 10.1016/j.tim.2017.09.004

Authors: Dylan H. Morris, Katelyn M. Gostic, Simone Pompei, Trevor Bedford, Marta Łuksza, Richard A. Neher, Bryan T. Grenfell, Michael Lässig, John W. McCauley

Institutions: Princeton University, University of California, Los Angeles, University of Cologne, Fred Hutch Cancer Center, Institute for Advanced Study, SIB Swiss Institute of Bioinformatics, University of Basel, National Institutes of Health, Fogarty International Center, The Francis Crick Institute

Language: English

Topic: Influenza Virus Research Studies

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: Wellcome Trust, Francis Crick Institute, Cancer Research UK, National Cancer Institute, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases, Eunice Kennedy Shriver National Institute of Child Health and Human Development

Awards: High-throughput experiments to guide influenza vaccine strain selection, Roles and Regulation of wild-type and mutant forms of p53, G3757071060, G6509507775, Epidemiological impacts of broadly protective childhood HA imprinting on seasonal and pandemic influenza, Infrastructure for the Office of Population Research, G8532923779, Real-time tracking of virus evolution for vaccine strain selection and epidemiological investigation

OpenAlex ID: W2765600556

FWCI: 1.375

Cites: 114

Cited by: 148

Related to: 10