Data Modelling

Management, modelling and biostatistics

Effective data management and biostatistics will support phenotypic multi-omics integration and modelling. 

Our data management will be led by the University of Potsdam supported by the teams at SSSA and IPK. The modelling will include detailed kinetic models of the Calvin Benson Cycle (CBC) to address current limitations. The model will build in steady state and then fluctuating light conditions. We will develop approaches for mapping multiple traits simultaneously and mechanistic models with the genomic data. The in silico analysis will be used to select genotypes for field trials and to suggest hypotheses for detailed testing under greenhouse conditions.

CAPITALISE will participate in the Pilot on Open Research Data using secure and compliant approaches incorporating the FAIR principles (findable, accessible, interoperable and re-useable). A permanent repository holding the CAPITALISE findings will support future biotechnology, crop breeding research and innovation activities.

Following publication relevant data, software and models will be made accessible to the scientific community. Plant biologists and crop breeders with an interest in maize, barley and tomato (and related crops) genotypes or phenotypes should find our data valuable. We will use a range of data sharing tools, including ELIXIR, the cross-domain data repository PGP (Plant Genomics and Phenomics Repository), Github, BioModels and BigModels. Contact us for updates on the development of our toolkit and access routes. 


Read more about


Calvin Benson cycle


Tuning Chl


Crop improvement