About

BALDR is an automated pipeline for biomarker comparison and prioritization in the context of diabetes. BALDR includes protein, gene and disease data from major public repositories, text-mining data and human and mouse experimental data from the IMI2 RHAPSODY consortium. These data are provided as easy-to-read figures and tables enabling direct comparison of up to 20 biomarker candidates for diabetes.

BALDR uses data from five major public databases: UniProt, PHAROS, Open Targets, DrugBank, and the Human Protein Atlas (HPA) that contain functional, interactional, and disease-relevant information for the human proteome. In BALDR, we utilize these data to inform on the relevance of proteins as novel, biologically relevant biomarkers for diabetes.

BALDR include observational and experimental data from the Risk Assessment and ProgreSsiOn of Diabetes (RHAPSODY) consortium, financed by EU Innovative Medicines Initiative-2. Within RHAPSODY, a large quantity of omics data has been generated, based on a federation of clinical cohorts that include patients in varying stages of diabetes, as well as human tissue analysis and mouse experiments conducted within the consortium.

Lastly, BALDR contains results from text mining of 15 million full text articles, protein-protein interaction data from STRING and gene enrichment information from WebGestaltR.

Translational Disease Systems Biology

The Brunak Group aims for understanding multi-morbidity disease progression patterns and their relation to treatment events. The group integrates heterogeneous life science data from the molecular and clinical domains and is also engaged in methodology of translational utility, such as techniques of relevance within precision medicine.
More information can be found on the University of Copenhagen website: https://cpr.ku.dk

Who?

Contact

Agnete Troen Lundgaard: agnete.lundgaard [at] cpr.ku.dk