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"Bayesian AnaLysis of Diabetes for Enhanced biomarkeR and drug target identification"

The BALDER project (2021-2023) aimed to develop a novel statistical software package that can help researchers identify new biomarkers and drug targets using already existing genomic data from Type 2 Diabetes Mellitus patients.

The team developed a mathematical approach called Multi-Trait Bayesian Linear Regression and implemented it into a software package. This package allows users to input genes of interest and apply various filters tailored to their needs. It assists users in interpreting existing data, revealing new connections, and identifying potential biomarkers and drug targets.

In the BALDER project, the team has taken advantage of the vast amount of genetic data from Type 2 Diabetes Mellitus patients that is already out there. These data has been used as a case study to demonstrate the usefulness of the software package. However, researchers can use the software for basically any disease of interest.

On this page you can can watch a video recorded at the beginning of the project. You can also read an article on the output of the project and you can find lists of project participants and articles published by the BALDER team.


Academic team members

  • Peter Sørensen, Senior Scientist, Aarhus University
  • Mads Fuglsang Kjølby, Assoc. Professor, Aarhus University
  • Palle Duun Rohde, Assoc. Professor, Aalborg University
  • Emily Somohardjo
  • Astrid Johannesson Hjelholt
  • Tahereh Gholipourshahraki
  • Zhonghao Bai
  • Merina Shrestha

Industrial team member

  • Joanna Howson, Novo Nordisk Reseearch Center 
  • Sile Hu, Novo Nordisk Reseearch Center 

"With the gact software package, we enable researchers to discover new connections between genetic entities, such as biological pathways, and complex traits, like diabetes.

All the users must do is to choose specific filters such as biological pathways or types of drugs. Depending on the filters used, the user will receive different output from the software. For instance, the software can provide new insights that can help the user identify or validate new biomarkers and drug targets."


Peter Sørensen, Head of the BALDER project


  1. Rohde PD et al. 2023. Expanded utility of the R package qgg with applications within genomic medicine. Bioinformatics 39:11. doi: https://doi.org/10.1101/2022.09.03.506466
  2. Bai Z, Gholipourshahraki T, Shrestha M, Hjelholt A, Rohde P, Kjolby M, Sørensen P. Evaluation of Bayesian Linear Regression Derived Gene Set Test Methods. doi: https://doi.org/10.1101/2024.02.23.581726
  3. Gholipourshahraki T, Bai Z, Shrestha M, Hjelholt A, Rohde P, Kjolby M, Sørensen P. Evaluation of Bayesian Linear Regression Models for Gene Set Prioritization in Complex Diseases. doi: https://doi.org/10.1101/2024.02.23.581718
  4. Shrestha M, Bai Z, Gholipourshahraki T, Hjelholt A, Rohde P, Kjolby M, Sørensen P. Evaluation of Bayesian Linear Regression Models as a Fine Mapping Tool. doi: https://doi.org/10.1101/2022.09.03.506466
  5. Kunkel D, Sørensen P, Shankar V, Morgante F. Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes. doi.org/10.1101/2024.05.06.592745


We unite right minds from industry and academia so that they can jointly create need-driven research projects - and pave the way for innovative new treatments in the future. Through competitive funding calls, we fund the best projects ideas. Although companies cannot receive funding, it is free of charge to join.

The 5-year platform is sponsored by the Novo Nordisk Foundation with 180 M DKK from 2024-2028.


You are always welcome to reach out if you have questions or comments. Reach out to odin@au.dk or find the Secretariat's direct email addresses under contacts.

Although we're spanning five Danish universities, we're based in Aarhus. Our office is located at Aarhus University, Ny Munkegade 121, blg 1521-216.