Using electronic biology based platform to predict flu vaccine efficacy for 2018/2019 [version 2; referees: 2 approved, 1 approved with reservations]
Flu epidemics and potential pandemics pose great challenges to public health institutions, scientists and vaccine producers. Creating right vaccine composition for different parts of the world is not trivial and has been historically very problematic. This often resulted in decrease in vaccinations...
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doaj-add5e2a7a34a4924a216af3af4e8625a2020-11-25T03:18:29ZengF1000 Research LtdF1000Research2046-14022018-05-01710.12688/f1000research.14140.216453Using electronic biology based platform to predict flu vaccine efficacy for 2018/2019 [version 2; referees: 2 approved, 1 approved with reservations]Slobodan Paessler0Veljko Veljkovic1Department of Pathology, Galveston National Laboratory, University of Texas Medical Branch at Galveston, Galveston , TX, USABiomed Protection, Galveston, TX, USAFlu epidemics and potential pandemics pose great challenges to public health institutions, scientists and vaccine producers. Creating right vaccine composition for different parts of the world is not trivial and has been historically very problematic. This often resulted in decrease in vaccinations and reduced trust in public health officials. To improve future protection of population against flu we urgently need new methods for vaccine efficacy prediction and vaccine virus selection.https://f1000research.com/articles/7-298/v2 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Slobodan Paessler Veljko Veljkovic |
spellingShingle |
Slobodan Paessler Veljko Veljkovic Using electronic biology based platform to predict flu vaccine efficacy for 2018/2019 [version 2; referees: 2 approved, 1 approved with reservations] F1000Research |
author_facet |
Slobodan Paessler Veljko Veljkovic |
author_sort |
Slobodan Paessler |
title |
Using electronic biology based platform to predict flu vaccine efficacy for 2018/2019 [version 2; referees: 2 approved, 1 approved with reservations] |
title_short |
Using electronic biology based platform to predict flu vaccine efficacy for 2018/2019 [version 2; referees: 2 approved, 1 approved with reservations] |
title_full |
Using electronic biology based platform to predict flu vaccine efficacy for 2018/2019 [version 2; referees: 2 approved, 1 approved with reservations] |
title_fullStr |
Using electronic biology based platform to predict flu vaccine efficacy for 2018/2019 [version 2; referees: 2 approved, 1 approved with reservations] |
title_full_unstemmed |
Using electronic biology based platform to predict flu vaccine efficacy for 2018/2019 [version 2; referees: 2 approved, 1 approved with reservations] |
title_sort |
using electronic biology based platform to predict flu vaccine efficacy for 2018/2019 [version 2; referees: 2 approved, 1 approved with reservations] |
publisher |
F1000 Research Ltd |
series |
F1000Research |
issn |
2046-1402 |
publishDate |
2018-05-01 |
description |
Flu epidemics and potential pandemics pose great challenges to public health institutions, scientists and vaccine producers. Creating right vaccine composition for different parts of the world is not trivial and has been historically very problematic. This often resulted in decrease in vaccinations and reduced trust in public health officials. To improve future protection of population against flu we urgently need new methods for vaccine efficacy prediction and vaccine virus selection. |
url |
https://f1000research.com/articles/7-298/v2 |
work_keys_str_mv |
AT slobodanpaessler usingelectronicbiologybasedplatformtopredictfluvaccineefficacyfor20182019version2referees2approved1approvedwithreservations AT veljkoveljkovic usingelectronicbiologybasedplatformtopredictfluvaccineefficacyfor20182019version2referees2approved1approvedwithreservations |
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1724626487894605824 |