Education Profile

  • Ph.D., University of Leipzig, 2009
  • M.Sc., University of Leipzig, 2005

Research Interests

​Professor Hoehndorf is interested in artificial intelligence, knowledge representation, biomedical informatics, ontology.

Selected Publications

  • Hoehndorf, R., Queralt-Rosinach, N., “Data science and symbolic AI: Synergies, challenges and opportunities”. In: Data Science.
  • Boudellioua, I., Mahamad Razali, R. B., Kulmanov, M., Hashish, Y., Bajic, V. B., Goncalves- Serra, E., Schoenmakers, N., Gkoutos, G. V., Schofield, P. N., Hoehndorf, R., “Semantic prioritization of novel causative genomic variants”. In: PLOS Computational Biology 13.4 (Apr. 2017), pp. 1–21.
  • Hoehndorf, R., Schofield, P. N., Gkoutos, G. V., “Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases”. In: Scientific Reports 5 (June 2015), p. 10888.
  • Robert Hoehndorf, Tanya Hiebert, Nigel W. Hardy, Paul N. Schofield, Georgios V. Gkoutos, and Michel Dumontier. "Mouse model phenotypes provide information about human drug targets". In: Bioinformatics (Oct. 2013).
  • Robert Hoehndorf, Paul N. Schofield, and Georgios V. Gkoutos. "PhenomeNET: a whole-phenome approach to disease gene discovery". In: Nucleic Acids Research 39.18 (July 2011), e119.