We seek to understand the organization of microbial communities and their role in mediating the global cycles of elements through the surface ocean.
Mathematical models and computer simulations allow us to encode an understanding of how the system works in a way which can make testable, quantitative predictions. CBIOMES researchers are collaborating to develop a hierarchy of models describing how the interactions of marine microbes with their environment and each other shapes their relative fitness; and how these interactions cumulatively shape the biogeography of the ocean and elemental cycles at the basin scale. In order to test and constrain these models we are compiling diverse, but relevant data, and developing tools with which to explore them. We are developing quantitative metrics and methods to bring together data and models.
Follow the links below to explore current projects and the people working on them:
Developing New Computational Modeling Frameworks
- Developing a New Trait-based Understanding of Microbial Communities Based on Metabolic and Elemental and Macromolecular Constraints (led by Zoe Finkel/Dal)
- Constraint-based Modeling of Marine Microbial Community Metabolism and Physiology (led by John Casey/MIT)
- Statistical Modeling of Microbial Communities: Niches, Traits, and Interactions (led by Andrew Irwin/Dal)
- Thermodynamically Constrained Metabolic Networks for Ocean Modeling (led by Joe Vallino/MBL)
- Models of Marine Microbial Biogeography and Biogeochemistry (led by Mick Follows and Stephanie Dutkiewicz/MIT)
Collecting and Compiling Relevant Datasets
- Ocean Color and Biogeochemistry (led by Shubha Sathyendranath/PML)
- Data and Tools to Define the Biogeography of Marine Microbes (led by Ginger Armbrust/UW)
- Microbial Growth, Interactions and Biogeographies from ‘Omics’ Data (led by Jed Fuhrman/USC)
Bringing Together Models with Data
- Advanced Statistical Analysis of Marine Microbial Systems (led by Christian Müller/Flatiron Institute)
- Unifying Data and Models through Biogeography (led by Chris Follett/MIT)
- Data Assimilative Modeling of Marine Ecosystems (led by Chris Edwards/UCSC)
- Statistical Network Inference and Time Series Analysis (led by Jacob Bien/USC)
CBIOMES User & Working Groups
Multiple self-organizing collaborations exist across and within CBIOMES however, as the collaboration has matured and evolved, larger working groups have coalesced around a number of topics. Other research-focused activities have resulted in the initiation of user groups. Our investigators also enjoy privileged access to Simons CMAP and its team of developers. Explore!
CBIOMES Research Highlights
CBIOMES contributions to the Annual Reports of the Simons Foundation Life Sciences Division
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