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Dietrich Rebholz-Schuhmann holds a chair in "Biomedical data analytics and semantics" at the Medical Faculty of the University of Cologne. His research focuses on the processing of semantic resources – for example terminologies, ontologies, meta-data and literature – that are relevant for data analytics in the life sciences. In more general terms, he applies data sciences technologies to numerical and semantics data across the full range of life sciences, including medicine, molecular biology, and related domains. The semantics approach in data analytics uses the integration of heterogeneous information and contributes to data interoperability.

In his research, Dietrich Rebholz-Schuhmann pursues innovative approaches such as automatic biomedical literature analysis, automatic data integration between scientific literature and biomedical databases and semi-automatic generation of new biomedical findings from integrated data. In genomics-driven cancer research, for example, his advanced work has paved the way for analyzing genomics variability in cancer tissue data through both interactive and automated means, enabling scientists to derive new findings for biomedical research.

Dietrich Rebholz-Schuhmann is the Scientific Director of ZB MED – Information Center for Life Sciences. He and his fellow researchers are striving to create an innovative infrastructure to act as a central hub for the international text mining research community. Their goal is to foster community-driven efforts to develop novel methods for data and information interoperability using knowledge graphs, the automatic annotation of data and information and the development and maintenance of terminologies and language systems.

Open ways to handle biomedical knowledge and scientific data: the use of knowledge graphs.

Selected publications

  1. Barros, J. M., Duggan, J., & Rebholz-Schuhmann, D. (2018). Disease mentions in airport and hospital geolocations expose dominance of news events for disease concerns. Journal of biomedical semantics, 9(1), 18.
  2. Jha, A., Khan, Y., Mehdi, M., Karim, M. R., Mehmood, Q., Zappa, A., ... & Sahay, R. (2017). Towards precision medicine: discovering novel gynecological cancer biomarkers and pathways using linked data. Journal of biomedical semantics, 8(1), 40.
  3. Karim, M. R., Michel, A., Zappa, A., Baranov, P., Sahay, R., & Rebholz-Schuhmann, D. (2017). Improving data workflow systems with cloud services and use of open data for bioinformatics research. Briefings in bioinformatics, 19(5), 1035-1050.
  4. Oellrich, A. et al. (2015). “The digital revolution in phenotyping”. In: Brief. Bioinformatics.
  5. Rebholz-Schuhmann, Dietrich et al. (2014). “Semantic integration of gene-disease associations for Diabetes Type II from literature and biomedical data resources”. In: Drug Discovery Today 19.7, pp. 882–9.
  6. Oellrich, A., R. Hoehndorf, G. V. Gkoutos, and D. Rebholz-Schuhmann (2012). “Improving disease gene prioritization by comparing the semantic similarity of phenotypes in mice with those of human diseases”. In: PLoS ONE 7.6, e38937.
  7. Rebholz-Schuhmann, D., A. Oellrich, and R. Hoehndorf (2012). “Text-mining solutions for biomedical research: enabling integrative biology”. In: Nat. Rev. Genet. 13.12, pp. 829–839.
  8. Hoehndorf, R., A. Oellrich, and D. Rebholz-Schuhmann (2010). “Interoperability between phenotype and anatomy ontologies”. In: Bioinformatics 26, pp. 3112–3118.
  9. Rebholz-Schuhmann, D. et al. (2010). “CALBC silver standard corpus”. In: Journal of bioinformatics and computational biology 8.1, pp. 163–179.
  10. Trieschnigg, D., P. Pezik, V. Lee, F. de Jong, W. Kraaij, and D. Rebholz-Schuhmann (2009). “MeSH Up: effective MeSH text classification for improved document retrieval”. In: Bioinformatics (Oxford, England) 25.11, pp. 1412–1418.