Five Blue-Cloud demonstrators are developed under the supervision of the French Research Institute for Exploitation of the Sea (IFREMER) with the aim of showcasing the potential of Blue-Cloud in different fields of marine science. The demonstrator “Plankton Genomics” is led by the European Bioinformatics Institute (EMBL-EBI), in collaboration with the Flanders Marine Institute (VLIZ) and the Faculty of Sciences at Sorbonne University.
Two Notebooks will analyse, model and map new plankton biogeographies in the Blue-Cloud infrastructure by combining molecular, imaging and environmental data types.
The composition and diversity of plankton communities are often used as an indicator of marine ecosystems health and their response to anthropic stressors.
Distinct archives and annotation tools exist for microscopic images, DNA sequences and environmental data, with generally high levels of maturity. However, the ocean science community lacks the support of platforms that integrate and compute data across these three domains.
Thanks to the Blue-Cloud environment, the demonstrator will showcase a deep assessment of plankton distributions, dynamics and fine-grained diversity to molecular resolution. Working across biomolecular, image and environmental data domains, and building on the outputs of existing initiatives, the “Plankton Genomics” demonstrator will focus on two main areas:
The demonstrator will work on datasets currently available via the following data infrastructures:
This demonstrator will bring a thorough understanding of the integration of data across microscopy imaging, molecular biology, and environmental platforms, including a knowledge of how future data should be collected and structured to allow cross-data type integration while retaining relevance and consistency within each respective data type.
The demonstrator will thus enable scientific exploration of plankton, including correlating plankton concentration and diversity with local environmental variables, deriving known and new indices of ecosystem health, and predicting the distribution of these variables in space and time.
Hear directly from representatives of EMBL-EBI and the Faculty of Sciences at Sorbonne University in this brief interview.