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Interpreting microbial growth rates from size distributions.
A multi-lab collaboration that grew out of the January 2020 Bayesian Workshop finds using the Bayesian approach can yield more realistic biological models and better constrained cellular growth rates. Continue reading “Interpreting microbial growth rates from size distributions.”
A Super-Speedy New Phytoplankton Model
CBIOMES researchers Zhen Wu and Gael Forget apply Julia to create a GPU-supported individual-based phytoplankton life cycle model.
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April 2022 CBIOMES e-meeting Zhen Wu (MIT)
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NEW CBIOMES PUBLICATION
Jann Paul Mattern, Kristof Glauninger, Gregory L. Britten, John R. Casey, Sangwon Hyun, Zhen Wu, E. Virginia Armbrust, Zaid Harchaoui, Francois Ribalet (2022), A Bayesian approach to modeling phytoplankton population dynamics from size distribution time series, PLoS Computational Biology, doi: 10.1371/journal.pcbi.1009733
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Significant organic carbon acquisition by Prochlorococcus in the oceans – Zhen Wu (MIT)
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NEW CBIOMES PUBLICATION
Zhen Wu, Stephanie Dutkiewicz, Oliver Jahn, Daniel Sher, Angelicque White, Michael J. Follows (2021), Modeling Photosynthesis and Exudation in Subtropical Oceans, Global Biogeochemical Cycles, doi: 10.1029/2021GB006941
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CBIOMES Goes to JuliaCon 2021
From agent-based models to exploring individual microbes and processes that drive species interactions to simulating planetary-scale transports that control ocean biogeography and climate change CBIOMES shared their Julia-based marine microbe and biogeochemical modeling know-how at this year’s Julia programming language conference.
The Follows Group goes to Annual Meeting 2021
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2021 Annual Meeting microtalk: PlanktonIndividuals.jl: A GPU supported individual-based phytoplankton life cycle model – Zhen Wu (MIT)
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