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Research focus

Matthias Heinig conducts research in the field of computational biology. His aim is the development and application of computational and statistical tools for the identification of molecular regulatory networks underlying common diseases and the genetic and epigenetic mechanisms controlling these networks from population level DNA, multi-omics and single cell data sets. A special focus is the molecular characterization of metabolic and cardiovascular diseases, in particular diabetes and arrhythmias like atrial or ventricular fibrillation.


 Genetics of complex traits Gene regulatory networks Personalized networksMachine Learning Big DataGWASeQTL

Professional Background

2006 - 2010

PhD, Max Delbrück Center for molecular medicine, Berlin

During my PhD I pioneered the use of regulatory networks for the interpretation of GWAS results.

2010 - 2015

Postdoc, Max Planck Institute of molecular genetics, Berlin

During my postdoc I elucidated the impact of sequence variants on the epigenome.

2015 - 2022

Junior group leader, Institute of Computational Biology, Helmholtz Munich

As junior group leader I developed methods to identify the molecular networks underlying common diseases from multi-omics and single cell data.


Tenured group leader

As tenured group leader I am working on personalizing regulatory networks as well as to identify disease core genes and on advancing the human heart cell atlas.


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2022 Nature Genetics

Hawe JS*, Wilson R*, Schmid KT*, Zhou L, Lakshmanan LN, Lehne BC, Kühnel B, Scott WR, Wielscher M, Yew YW, Baumbach C, Lee DP, Marouli E, Bernard M, Pfeiffer L, Matías-García PR, Autio MI, Bourgeois S, Herder C, Karhunen V, Meitinger T, Prokisch H, Rathmann W, Roden M, Sebert S, Shin J, Strauch K, Zhang W, Tan WLW, Hauck SM, Merl-Pham J, Grallert H, Barbosa EGV; MuTHER Consortium, Illig T, Peters A, Paus T, Pausova Z, Deloukas P, Foo RSY, Jarvelin MR, Kooner JS, Loh M†, Heinig M†, Gieger C†, Waldenberger M†, Chambers JC†

Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function

Networks and Affiliations