Pattern Recognition, Data Analysis, Bioinformatics, Signal Analysis, Experimental Design
My interests are in data analysis, primarily pattern recognition, but also signal analysis and experimental design, as applied to data, primarily from analytical instrumentation e.g. biomarker discovery and diagnosis, metabolomic profiling, data mining of biomedical databases and microbiology. I am currently especially interested in developing approaches such as Support Vector Machines and Self Organising maps, but am experienced in more traditional approaches such as experimental design and multivariate statistics.
I am available either as a private consultant or via my employer, the University of Bristol.
I am a fellow of the Royal Society of Chemistry, Royal Society of Medicine and Royal Statistical Society.
I have authored 334 publications, of which 4 are authored and 3 edited books, and 151 are refereed papers. I have given 155 invited lectures (conferences and seminars) in 29 countries worldwide. My work has been cited 2,244 times. I have had 122 coworkers in my group over a period of around 20 years. Grant income has been over £1,000,000 direct to my group (some as part of large consortia worth many times this) and around £2,000,000 including fees and workshop income.
Since 2005 I have worked productively with the following organisations (all resulting in joints papers or successfully funded work or expert consultancy / evidence)
• UK : Glaxo Smith Kline, Mass Spec Analytical, Triton Technology, University of Bolton, London South Bank University, University of Newcastle, Unilever, Crown Prosecution Service, Her Majesty’s Revenue and Custom, British Library, Assets Recovery Agency.
• Austria : Konrad Lorentz Institute, University of Vienna, Medical University of Vienna
• Germany : Vermicon Ltd
• Hungary : Corvinus University
• US : University of Indiana, Johns Hopkins University, Draper Research Laboratories
• Pakistan : Pakistan Institute of Nuclear Science and Technology, Quaid-i-Azam University.
A few examples of recent publications are as follows.
1. R.G.Brereton, Applied Chemometrics for Scientists, Wiley, Chichester, xv + 379 pp., 2007
2. R.G.Brereton, Chemometrics for Pattern Recognition, Wiley, Chichester, 2009
3. K. Wongravee, G.R. Lloyd, C. J. Silwood, M. Grootveld, R.G. Brereton, Supervised Self Organizing Maps for classification and determining potentially discriminatory variables: illustrated by application to NMR metabolomic profiling, Analytical Chemistry, 82, 629-639 (2010)
4. S. Zomer, S. J. Dixon, Y. Xu, S. P. Jensen, H. Wang, C. V. Lanyon, A. G. O'Donnell, A. S. Clare, L. M. Gosling, D. J. Penn, R. G. Brereton, Consensus Multivariate methods in Gas Chromatographic Mass Spectrometry and Denaturing Gradient Gel Electrophoresis : MHC-congenic and other strains of mice can be classified according to the profiles of volatiles and microflora in their scent-marks, Analyst, 134, 114-123 (2009)
5. M. L. Schaefer, K. Wongravee, M. E. Holmboe, N. M. Heinrich, S. J. Dixon, J. E. Zeskind, H. M. Kulaga, R. G. Brereton, R. R. Reed, J. M. Trevejo, Mouse urinary biomarkers provide signatures of maturation, diet, stress level, and diurnal rhythm, Chemical Senses, in press (2010)
6. Y.Xu, S.J.Dixon, R.G.Brereton, H.A.Soini, M.V.Novotny, K.Trebesius, I.Bergmaier, E.Oberzaucher, K.Grammer, D.J.Penn, Comparison of human axillary odour profiles obtained by gas chromatography mass spectrometry and skin microbial profiles obtained by denaturing gradient gel electrophoresis using multivariate pattern recognition, Metabolomics, Metabolomics, 3, 427-437 (2007)
7. Y.Xu, R.G.Brereton, , Diagnostic pattern recognition on Gene Expression Profile Data by using One-Class Classification, , J. Chem. Inf. Modelling, , 45, 1392-1401 (2005)
8. R.G.Brereton, M.Devonshire, Genotyping using Single Nucleotide Polymorphism, Fluorescence Spectroscopy and Pattern Recognition, Analyst, 129, 249-253 (2004)
9. S.J.Dixon, Y.Xu, R.G.Brereton, A.Soini , M.V.Novotny, E.Oberzaucher, K.Grammer, D.J.Penn, Pattern Recognition of Gas Chromatography Mass Spectrometry of Human Volatiles in Sweat to distinguish the Sex of Subjects and determine potential Discriminatory Marker Peaks, Chemometrics Intell. Lab. Systems, 87, 161–172 (2007)
A recent cv is attached.