Professor Georgios V. Gkoutos PhD, DIC

Institute of Cancer and Genomic Sciences
Chair of Clinical Bioinformatics

Contact details

Centre for Computational Biology
Haworth Building
University of Birmingham
B15 2TT

George Gkoutos is a Professor of Clinical Bioinformatics with interests in the general areas of clinical and biomedical informatics, computational biology, and integrative and translational research aiming at the discovery of molecular origins of human disease and the development of novel diagnostic and intervention strategies.


  • Ph.D. in Molecular and Biological Informatics, Imperial College, 2002
  • MSc. in Computational Biology, University of Essex, 1999
  • BSc (Hons) in Biochemistry, University of Essex, 1998


A biochemist by training, George was initially involved in the field of Computational Biology following a MSc degree by research on correlated mutations analysis on G-Protein coupled receptors which involved modelling class A G-Protein Coupled Receptors (GPCRs) and drug design. He then proceeded to obtain a PhD in the areas of Chemoinformatics/Bioinformatics at Imperial College of London.

After the completion of his PhD, he was awarded a MRC Career Development Fellowship at MRC Harwell, Oxford. In 2005, he joined the Department of Genetics at Cambridge University and was part of various international consortia aimed at facilitating the translation of basic research findings to applications that aimed at the identification of the genetic underpinnings of disease mechanisms. In 2012, he became the head of the Bioinformatics and Computational Biology Group at Aberystwyth University, an interdisciplinary group of bioinformatics researchers, working at the interface between computing, biology and medical applications and crossing the Department of Computer Science and the Institute of Biological, Environmental and Rural Sciences (IBERS). George maintains an Aberystwyth University honorary Professorship in Bioinformatics.

In September 2015, George joined the University of Birmingham as the Chair of Clinical Bioinformatics. Professor Gkoutos splits his time between the Centre of Computational Biology, the College of Medical and Dental Sciences, the Institute of Translational Medicine and the Queen Elizabeth Hospital.


Professor Gkoutos's main research lies within the areas of clinical and biomedical informatics, computational biology, and translational research aiming at the discovery of molecular origins of human disease and the development of novel disease diagnostic and intervention strategies. It involves methods stemming from integrative systems biology, biomedical knowledge formalization, standardisation and representation, large data integration and analysis, comparative phenomics, chemical and clinical informatics. The primary areas of applications include semantic representation, integration and analysis of big data, enabling the translation of data across species, domains and levels of granularity with application on the investigation of the pathophysiology and pathobiology of human disease, and pharmacogenomics.

Other activities

  • Honorary Professor of Bioinformatics, University of Aberystwyth
  • Member of the Medical Research Council's Skills Development Panel


de Angelis, MH,, (2015) Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics. Nature Genetics. Sep;47(9):969-78

Hoehndorf, R, Schofield, PN, and Gkoutos, GV, (2015), Analysis of the human diseasome using phenotype similarity, between common, genetic, and infectious diseases, Nature Scientific Reports, Jun 8;5:10888. doi: 10.1038/srep10888.

Hoehndorf, R, Schofield, PN, and Gkoutos, GV, (2015), The role of ontologies in biological and biomedical research: a functional perspective, Briefings in Bioinformatics, Nov;16(6):1069-80.

Deans, A,, Finding our way through phenotypes, Plos Biology, 2015, Jan 6;13(1):e1002033.

Hoehndorf, RT. Hiebert, N. Hardy, P. Schofield, G. V. Gkoutos, Mouse model phenotypes provide information about human drug targets, Bioinformatics, 2014, 30(5): 719-25.

Köhler S,,The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res. (2014), Jan 42.

Hoehndorf, R, Schofield, PN, and Gkoutos, GV. (2013), An integrative, translational approach to understanding rare and orphan genetically based diseases, Interface Focus, Apr 6;3(2):20120055

Doelken, C, (2013), Phenotypic overlap in the contribution of individual genes to CNV pathogenicity revealed by cross-species computational analysis of single-gene mutations in humans, mice and zebrafish, Mar;6(2):358-72.