FindingPheno
The University of Copenhagen
Copenhagen, Denmark
The University of Copenhagen (UCPH) was founded in 1479 and today has approximately 39,000 students and 9,000 employees – of whom about 5,000 are researchers, making it the largest research and educational institution in the Nordic countries. The diversity of research programs and scientific expertise at UCPH is a distinguishing feature of the university.
The UCPH researchers participating in FindingPheno come from two departments, The Globe Institute and the Department of Mathematical Sciences. The combined expertise of these UCPH researchers spans applied statistics, machine learning, evolutionary genomics, population genomics and industrial microbiome research.
FindingPheno is coordinated by the Section of HoloGenomics (SH) at The GLOBE Institute. Globe is an interdisciplinary research institute interested in how things begin, with research spanning ancient DNA, evolutionary genomics, microbiomes, climate change, geobiology, and planet formation. Within this institute, the SH is a hotbed of genomic and metagenomic research and includes pioneers of the hologenomics theory on interactions between host and microbiomes. FindingPheno PIs at The Globe are Assoc. Prof. Shyam Gopalakrishnan, head of the Population and Statistical Genetics Group, and Assoc. Prof. Fernando Racimo, head of The Racimo Lab focusing on adaptation, admixture and ancient DNA.
FindingPheno also includes researchers from the Section for Statistics and Probability Theory (SPT) at The Department of Mathematical Sciences. A main theme at the SPT is statistical inference from discrete time sampling of continuous time processes, including biostatistics applications such as gene expression data, DNA data and stochastic neuronal models. The SPT PIs in FindingPheno, Prof. Helle Sørensen and Assoc. Prof. Bo Markussen, are both involved in The Data Science Lab, a cross-department initiative to enhance the quality of UCPH data analyses via training and new method development in applied statistics.
UCPH researchers have access to the Danish life sciences supercomputing facility, computerome, the danish node of the European ELIXIR computing infrastructure, providing the infrastructure and support necessary to conduct large-scale multi-omics analyses.
Project Contributions
UCPH lead WP5 to develop a hierarchical Bayesian framework that integrates existing biological knowledge with the omics data sets to create an inference model for predicting phenotype outcomes. In addition, they contribute novel structural causal models to WP3, adding directionality to the relationships identified by Machine Learning to give true causality (a causes b) rather than just associations (a and b are somehow related).
As the coordinating partner, UCPH also leads the Project Management (WP8) and Dissemination (WP1) work packages with strong involvement from all other partners.
