An integrative, translational approach to understanding rare and orphan genetically based diseases

Robert Hoehndorf*, Paul N. Schofield, Georgios V. Gkoutos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


PhenomeNet is an approach for integrating phenotypes across species and identifying candidate genes for genetic diseases based on the similarity between a disease and animal model phenotypes. In contrast to 'guilt-byassociation' approaches, PhenomeNet relies exclusively on the comparison of phenotypes to suggest candidate genes, and can, therefore, be applied to study the molecular basis of rare and orphan diseases for which the molecular basis is unknown. In addition to disease phenotypes from the Online Mendelian Inheritance in Man (OMIM) database, we have nowintegrated the clinical signs from Orphanet into PhenomeNet.We demonstrate that our approach can efficiently identify known candidate genes for genetic diseases in Orphanet and OMIM. Furthermore, we find evidence that mutations in the HIP1 gene might cause Bassoe syndrome, a rare disorder with unknown genetic aetiology. Our results demonstrate that integration and computational analysis of human disease and animal model phenotypes using PhenomeNet has the potential to reveal novel insights into the pathobiology underlying genetic diseases.

Original languageEnglish (US)
JournalInterface Focus
Issue number2
StatePublished - Apr 6 2013
Externally publishedYes


  • Animal model
  • Biomedical informatics
  • Orphan disease
  • Orphanet
  • Phenotype
  • Rare disease

ASJC Scopus subject areas

  • Biotechnology
  • Biophysics
  • Bioengineering
  • Biochemistry
  • Biomaterials
  • Biomedical Engineering


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