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Biocuration for Digital Health

Advances in medical research revealed that a disease phenotype is the result of pathobiological processes that interact in complex networks.

Advances in medical research revealed that a disease phenotype is the result of pathobiological processes that interact in complex networks.

What We Do

Our aim is to generate high-quality databases that describe experimentally validated interactions between molecules and processes involved in the development of diseases. A large body of information that was generated in decades of experimental research is hidden in the scientific literature. In our group, experienced curators extract knowledge from scientific articles and collect information in structured and user-friendly databases. The second focus of the group is the generation of interaction networks in collaborations with experimentally working groups, in for particular for type 2 diabetes, neurologic and cardiovascular diseases.

Group Members

Herr Ruepp, Andreas Dr.

Dr. Andreas Ruepp

Group Leader, Research Group 'Biocuration for Digital Health' View profile

Barbara Brauner

Dr. Gisela Fobo

Dr. Goar Frischmann

Dr. Corinna Montrone

Database Projects

Systems biology and network medicine approaches require trustworthy, high-quality databases for the analysis of their experimentally generated results. Our group offers a set of manually curated databases with user-friendly web interface, graphical analysis tools and datasets available for download.


Comprehensive Resource of Mammalian Protein Complexes


The CORUM database provides comprehensive reference information about experimentally characterized, mammalian protein complexes. The new CORUM 4.0 release encompasses 5204 protein complexes offering the largest and most comprehensive publicly available, manually curated dataset in the field. In addition to various kinds of data analyses, CORUM is a broadly used information resource which is applied in more than 50 biomedical databases and research tools.


Multifactorial Interaction Networks in Human Diseases


The pathobiology of common diseases is influenced by heterogeneous factors interacting in complex networks. CIDeR is a publicly available, manually curated, integrative database of type 2 diabetes as well as other metabolic and neurological disorders. Systematic annotation and interactive graphical representation of disease networks make CIDeR a versatile knowledge base for biologists, analysis of large-scale data and systems biology approaches.


Comprehensive Database for Phenotypic Characterization of Rare Cardiac Diseases


PhenoDis provides a comprehensive characterization of 307 rare cardiac diseases with an emphasis on the phenotypic description. Prediction of diseases and disease-causing genes is facilitated by using the Human Phenotype Ontology (HPO) which is applied by the vast majority of computational approaches in the field.


Manual Curation of Disease Networks

In collaboration with experimentally working groups, we are performing deep curation of relevant literature. The results enable us to create multifactorial interaction networks connecting experimental data with biological context and generating testable hypothesis. Below, results from three exemplary collaborations are shown.



Metformin is used as a first-line oral treatment for type 2 diabetes. To investigate the underlying molecular mechanisms of metformin, metabolomic and genomic data of the population-based KORA cohort were analyzed in collaboration with the group of Rui Wang-Sattler. By applying in-depth curation, we found experimental evidence in the literature that point to a liver-specific pathway for metformin activity. In agreement with this model, the drug does not inhibit but activate the activity of AMPK in liver .





The molecular pathophysiology that links SARS-CoV-2 infection to the clinical manifestations and course of COVID-19 is complex and spans multiple biological pathways, cell types and organs. To gain the insights into this complex network, we participated in a collaborative effort involving over 230 biocurators from 30 countries to develop the COVID-19 Disease Map, an open-access collection of curated computational diagrams and models of molecular mechanisms implicated in the disease.



Human Endogeneous Retroviruses


Human endogenous retroviruses (HERVs) belong to the long terminal repeat (LTR) family of retrotransposons and comprise 8% of the human genome. Many recent studies provided compelling evidence that HERVs critically influence biological processes, including placenta development or pluripotency of stem cells. In a collaboration with the group of Michelle Vincendeau from the institute of virology we could show that the activation of HERV-K(HML-2) disrupts cortical patterning and neuronal differentiation by increasing NTRK3.


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Herr Ruepp, Andreas Dr.

Dr. Andreas Ruepp

Group Leader, Research Group 'Biocuration for Digital Health'