Professor Georgios V. Gkoutos PhD, DIC, FRSB, FRSM

Professor Georgios V. Gkoutos

Institute of Cancer and Genomic Sciences
Chair of Clinical Bioinformatics, Joint Director of the Centre for Health Data Science
Associate Director of HDRUK Midlands, Deputy Director of the Centre for Environmental Research and Justice
Programme Director for Health Data Science

Contact details

Centre for Health Data Science
IOEM Building
University of Birmingham
B15 2TT

Professor Gkoutos holds the chair of Clinical Bioinformatics, a joint appointment between the University of Birmingham Medical School and the University Hospitals Birmingham NHS Foundation Trust. 

He is the Joint Director of the Health Data Science Centre at the University of Birmingham, a Faculty Affiliate Professor of Clinical Bioinformatics, Berkeley Lab, Associate Director of MRC Health Data Research UK, Co-Director of the WCH-Birmingham Research Institute, Alan Turing Fellow and a Fellow of the Robinson College at University of Cambridge.


  • D.I.C., Imperial College, 2002
  • PhD 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, and in September 2015, George joined the University of Birmingham as the Chair of Clinical Bioinformatics. Professor Gkoutos splits his time between the Centre for Health Data Science, the College of Medical and Dental Sciences, the Institute of Translational Medicine, and the Queen Elizabeth Hospital.



Professor Gkoutos's research background lies within the areas of clinical and biomedical informatics, health data science and translational research aiming at the discovery of molecular origins of human disease and the development of novel disease diagnostic and intervention strategies. His expertise lies in the fields of translational phenomics, integrative systems biology, biomedical knowledge formalization, standardisation and representation, multimodal large data harmonization, interoperability and integration, Artificial Intelligence and Machine Learning, and multiomics, multimodal integrative analytics.

He has over 200 peer reviewed publications [total grant funding (last 5 years) < £60M, personal <5.2 million] and is closely involved with international efforts to integrate large phenotype datasets from the main high throughput phenotyping centres in Europe, Australasia and North America, and policy development in data and resource standards and sharing.

Other activities


  • Fellow, Robinson College, University of Cambridge
  • Fellow of the Royal Society of Medicine
  • Fellow of the Royal Society of Biology
  • Fellow of the Alan Turing Institute

Editorial Boards

  • Member of the Computers in Biology and Medicine
  • Member of the Editorial Board of Genes
  • Member of the Editorial Board of Plos ONE
  • Member of the Editorial Board of ASSAY and Drug Development Technologies
  • Member of the Editorial Board Precision Clinical Medicine Journal

External Engagement

  • 2023 - External Examiner postgraduate and undergraduate degrees - University of Manchester
  • 2020 - Expert Member of COST Harmonizing Information / Artificial Intelligence
  • 2020 - Expert Member of COST Harmonizing cancer research and -omics practice
  • 2016 - Member of the NHS GMCs & GEL Genomic data panel

National Boards and Committees

2022 - co-Chair of the BBSRC CCN panel
2017 - Member of NIHR Advanced Fellowship Panel
2016 - 2017 Member of the Medical Research Council Skills Development Panel
Senior Promotions Panels - most recent University College London (2021)

Honorary Posts 

  • Faculty Affiliate Professor Lawrence Berkeley National Laboratory, USA 
  • Honorary Professor, UCCS, University of Hamburg, Germany
  • Professor of Bioinformatics, University Hospitals Birmingham, NHS Foundation Trust 
  • Honorary Professor of Bioinformatics, University of Aberystwyth


Kotecha D, et al. (2022) CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research., BMJ. 378: e069048.

Subramanian A. (2022) Symptoms and risk factors for long COVID in non-hospitalized adults, Nat Med. Jul 25. doi: 10.1038/s41591-022-01909-w

Karwath A., (2021) Redefining beta-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: A novel machine learning approach to clustering., Oct 16;398(10309):1427-1435

Chua W., (2021) Quantification of fibroblast growth factor 23 and N-terminal pro-B-type natriuretic peptide to identify patients with atrial fibrillation using a high-throughput platform: A validation study, Plos Medicine, Feb 3;18(2):e1003405.

Xu Y  (2021), CACONET: a novel classification framework for microbial correlation networks, Bioinformatics. 2022 Jan 4:btab879

Chapman M, (2021), Desiderata for the development of next-generation electronic health record phenotype libraries, GigascienceSep 11;10(9):giab059.

Wang J., (2021), Fractal Analysis: Prognostic Value of Left Ventricular Trabecular Complexity Cardiovascular MRI in Participants with Hypertrophic Cardiomyopathy, Radiology, Jan;298(1):71-79.

Carr et al (2021), Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study, BMC Med, Jan 21;19(1):23.

Chua, W., et al., (2019) Data-driven discovery and validation of circulating blood-based biomarkers associated with prevalent atrial fibrillation, 2019, Eur Heart J. 7. doi: 10.1093/eurheartj/ehy815

Leighton, S, (2019), Development and validation of multivariable prediction models of remission, recovery and quality of life outcomes in people with first episode psychosis - a machine learning approach, The Lancet Digital Health., 1, 6, e261-e270

View all publications in research portal