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Professor Michael Barnes

Michael

Professor of Bioinformatics and Director of the Centre for Translational Bioinformatics

Centre: Clinical Pharmacology and Precision Medicine, Translational Bioinformatics

Email: m.r.barnes@qmul.ac.uk
Telephone: +44(0) 20 7882 2059
Website: https://www.qmul.ac.uk/c4tb/
Twitter: @thebarneslab

Profile

Michael co-leads the Centre for Translational Bioinformatics (C4TB), at Queen Mary University of London and is a Fellow of the Digitial Environment Research Institute, QMUL. His team work across diverse research areas, including genomics, drug discovery, stratified medicine, machine learning and health informatics with a unified objective to drive forward translation into the clinic. He brings an industrial perspective to the C4TB, drawn from 16 years of leadership of bioinformatics teams in the pharmaceutical industry.

Michael is a Fellow of the Alan Turing Institute and an HDR-UK Investigator, and co-leads the Genomics England Stratified medicine genomic interpretation clinical partnership. He has an active portfolio of stratified medicine projects as a co-investigator and data integration lead on several MRC projects, including MRC PSORT (Psoriasis), MRC RA-Map (RA), MRC MATURA (RA), and CLUSTER (Juvenile Arthritis). He also co-leads the NIHR AI-Multiply Consortium which is using AI to investigate the relationship between multiple long-term conditions and polypharmacy. He has served on the MRC Methodology Research Panel and Stratified Medicine panels and also advises on a number of project boards, including the UnitedHealth Group Pharmacogenetics advisory group, the Dutch Heart Foundation, the MRC-eMedLab HPC Cloud facility, the IMI etriks project, and the F1000 faculty. 

Research

Group members
Research staff: Claudia Cabrera, Rafael Henkin, Sandra Ng, Alisha Angdembe
PhD Students: Hannah Nicholls, Ruchi Upmanyu, Sara Maserone, Katriona Goldmann, Amaya Syed

Summary

Dr Barnes has broad computational biology research interests spanning the translational research and drug discovery continuum, from genetic and genomic methods for target identification to clinical informatics, patient stratification and multiple long term conditions. Active research projects in his team fall into the following key areas:

  • Pathway analysis of Genetic and Genomic data: Genome-wide association studies (GWAS) and exome studies of complex trait pathology and drug response, including, Hypertension, Arrhythmia and Cardiovascular disease.
  • Exome and Whole Genome Re-sequencing: NGS pipeline development, Re-sequencing studies, causal variant identification and functional analysis.
  • Multi-Omics and Stratified Medicine: RNA-seq based transcriptomic analysis, proteomics and epigenomics for biomarker identification and stratification of medicine response in Inflammatory diseases.
  • Trauma Injury Research: Transcriptomic and epigenomic analysis of early response to trauma injury as determinant of patient clinical trajectory in critical care. 
  • Chemogenomics and Drug Discovery: Target identification and druggability assessment, Chemogenomic analysis and connectivity map analysis. Drug Repositioning.
  • AI for Multiple Long Term Conditions (MLTC): Application of AI methods to MLTC research to explore MLTC pathology and identify intervention points.  
  • Clinical Informatics: Development of Clinical datamarts to support translational research and stratified medicine. Currently developing i2b2 and TranSMART based systems.
  • Cloud Computing: Development of virtual machine infrastructure for flexible scientific cloud computing across omics and clinical informatics applications. 
  • AI and Machine Learning: Development and application of explainable machine learning and AI methodology to clinical and genomic data. 

Key Publications

Full list of publications 

  1. RA-MAP consortium (2022) RA-MAP, molecular immunological landscapes in early rheumatoid arthritis and healthy vaccine recipients. Scientific data 9 (1), 196
  2. Hunt GP, Grassi L, Henkin R, Smeraldi F, Spargo TP, Kabiljo R, Koks S, Ibrahim Z, Dobson RJB, Al-Chalabi A, Barnes MR, Iacoangeli A. (2022)  GEOexplorer: a webserver for gene expression analysis and visualisation. Nucleic Acids Res. 50(W1):W367-74.
  3. Rivellese F, Surace AEA, Goldmann K, Sciacca E, Çubuk C, Giorli G, John CR, Nerviani A, Fossati-Jimack L, Thorborn G, Ahmed M, Prediletto E, Church SE, Hudson BM, Warren SE, McKeigue PM, Humby F, Bombardieri M, Barnes MR, Lewis MJ, Pitzalis C; R4RA collaborative group.  (2022) Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial. Nat Med. 28(6):1256-1268.
  4. Smedley et al (2021) Impact of the 100,000 Genomes Pilot on rare disease diagnosis in healthcare, New England Journal of Medicine,  385(20):1868-1880.
    Geifman N, PSORT Consortium et al (2021). Defining trajectories of response in patients with psoriasis treated with biologic therapies. Br J Dermatol. 2021 Apr 7.
  5. John CR, Watson D, Russ D, Goldmann K, Ehrenstein M, Pitzalis C, Lewis M, Barnes M (2020) M3C: Monte Carlo reference-based consensus clustering. Sci Rep. 10(1):1816.
  6. John CR, Watson D, Barnes MR, Pitzalis C, Lewis MJ. Bioinformatics (2020) Spectrum: Fast density-aware spectral clustering for single and multi-omic data. Bioinformatics 36(4):1159-1166.
  7. Lewis MJ, Barnes MR et al (2019) Molecular Portraits of Early Rheumatoid Arthritis Identify Clinical and Treatment Response Phenotypes. Cell Rep. 28(9):2455-2470
  8. Watson DS, Bruce IN, Griffiths CE, McInnes IB, Barnes MR*, Floridi L*. (2019) Clinical applications of machine learning algorithms: beyond the black box. BMJ. 364:l886 (* snr author)
  9. Dand N et al (2019) HLA-C*06:02 genotype is a predictive biomarker of biologic treatment response in psoriasis. J Allergy Clin Immunol. 143(6):2120-2130.
  10. Foulkes et al (2018) A framework for multi-omic prediction of treatment response to biologic therapy for psoriasis, J Invest Dermatol. S0022-202X(18)32355-8 (last author)
  11. Lewis M and Barnes MR (2018) RNA sequencing and machine learning as molecular scalpels. Nature Reviews Rheumatology, 14(7):388-390. 

Sponsors

Collaborators

Internal
Prof Mark Caulfield (WHRI); Prof Costantino Pitzalis (WHRI); Prof Leo Dunkel (WHRI); Prof Patricia Munroe (WHRI); Prof David Kelsell (Blizard); Prof Amrita Ahluwalia (WHRI); Prof Karim Brohi (Blizard); Prof David Van Heel (Blizard); Prof Silvia Marino (Blizard); Prof Sussan Nourshagh (WHRI); Prof Rupert Pearse (WHRI); Prof Steffen Petersen (WHRI); Prof Adam Timmis (WHRI); Dr Michael O'Dwyer (WHRI); Dr Myles Lewis (WHRI)

External
Prof Nick Reynolds (Newcastle); Prof John Issacs (Newcastle); Prof Christopher Griffiths (Manchester); Prof Ann Morgan (Leeds); Prof Folkert Asselbergs (UCL); Dr Brendan Keating (UPENN); Prof Jo Knight (Lancaster); Dr Michael Weale (KCL); Dr Gerome Breen (Institute of Psychiatry, KCL); Prof Gerhard Ecker (University of Vienna)

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