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https://www.selleckchem.com/products/17-AAG(Geldanamycin).html Data and information technology are key to every aspect of our response to the current COVID-19 pandemic-from how we diagnose patients and deliver care, to the development of predictive models of disease spread, to the management of personnel and equipment. The increasing engagement of informaticians at the forefront of these efforts has been a fundamental shift from an academic to an operational role. However, the past history of informatics as a scientific domain and an area of applied practice provides little guidance or prologue for the incredible challenges that we are now tasked with performing. Building upon our recent experiences, we present four critical lessons-learned that have helped shape our scalable, data-driven response to COVID-19. We describe each of these lessons within the context of specific solutions and strategies we applied in addressing the challenges that we faced. © The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email journals.permissions@oup.com.BACKGROUND AND AIMS Understanding how plant allometry, plant architecture, and phenology contribute to fruit production can identify those plant traits that maximize fruit yield. In this study, we compared these variables and fruit yield for two shrub species, Vaccinium angustifolium and Vaccinium myrtilloides to test the hypothesis that phenology is linked to the plants' allometric traits, which are predictors of fruit production. METHODS We measured leaf and flower phenology and the aboveground biomass of both Vaccinium sp. in a commercial wild lowbush blueberry field (Quebec, Canada) over a two-year crop cycle; one year of pruning followed by one year of harvest. Leaf and flower phenology were measured, and the allometric traits of shoots and buds were monitored over the crop cycle. We hand-collected the fruits of each p

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