Our research has been highly inter- and multi-disciplinary and we have worked at the interface between Analytical Chemistry/Biotechnology, Biology (Microbial Physiology and Systematics) and Mathematics/Computation (Chemometrics/Machine Learning).  Since 1992 we have contributed to a number of world firsts, in particular:

•  The first demonstration that neural networks could be used to analyse pyrolysis mass spectra; this was deemed significant enough to be published as a scientific correspondence in Nature.
  Goodacre, R., Kell, D.B. and Bianchi, G. (1992) Neural networks and olive oil. Nature 359, 594-594.
   

•  The first demonstration that quantitative information could be extracted from pyrolysis mass spectra by applying neural networks and partial least squares, this has led to their widespread use with biotechnology.
  Goodacre, R. and Kell, D.B. (1993) Rapid and quantitative analysis of bioprocesses using pyrolysis MS and neural networks - application to indole production. Anal. Chim. Acta 279, 17-26.
  Goodacre, R., Neal, M.J. and Kell, D.B. (1994) Rapid and quantitative analysis of the pyrolysis mass spectra of complex binary and tertiary mixtures using multivariate calibration and artificial neural networks. Anal. Chem. 66, 1070-1085.
   

•  First patented (#WO 96/42058, US5946640) demonstration that neural networks may be used to effect a robust correction for drift in instruments producing highly multivariate data.
  Goodacre, R. and Kell, D.B. (1996) Correction of mass spectral drift using artificial neural networks. Anal. Chem. 68, 271-280.
   

• Development of the DRASTIC (Diffuse reflectance absorbance spectroscopy taking in chemometrics) method for the rapid and non-invasive screening of microbial fermentations, which is a 100-fold faster than conventional methods.
  Winson, M.K., Goodacre, R., Woodward, A.M., Timmins, É.M., Jones, A., Alsberg, B.K., Rowland, J.J. and Kell, D.B. (1997) Diffuse reflectance absorbance spectroscopy taking in  chemometrics (DRASTIC). A hyperspectral FT-IR-based approach to rapid screening for metabolite overproduction. Anal. Chim. Acta 348, 273-282.
   

• The development and first exploitation of genetic programming for the analysis of spectroscopic data.
  Gilbert, R.J., Goodacre, R., Woodward, A.M. and Kell, D.B. (1997) Genetic programming: a novel method for the quantitative analysis of pyrolysis mass spectral data. Anal. Chem. 69, 4381-4389.
   

• The first demonstration that dispersive Raman spectrometry can be used to identify bacteria.
  Goodacre, R., Timmins, É.M., Burton, R., Kaderbhai, N., Woodward, A.M., Kell, D.B. and Rooney, P.J. (1998) Rapid identification of urinary tract infection bacteria using hyperspectral, whole organism fingerprinting and artificial neural networks. Microbiol. 144, 1157-1170.
   

• The first demonstration that the combination of whole organism fingerprinting with neural networks can provide very rapid and accurate antibiotic susceptibility testing.
  Goodacre, R., Rooney, P.J. and Kell, D.B. (1998) Discrimination between methicillin-resistant and methicillin-susceptible Staphylococcus aureus using pyrolysis mass spectrometry and artificial neural networks. J. Antimicr. Chemother. 41, 27-34.
  Goodacre, R., Rooney, P.J. and Kell, D.B. (1998) Rapid analysis of microbial systems using vibrational spectroscopy and supervised learning methods: application to the discrimination between methicillin-resistant and methicillin-susceptible Staphylococcus aureus. In: Proc. of SPIE's BiOS '98 - International Biomedical Optics Symposium: Infrared Spectroscopy: New Tool in Medicine, Vol. 3257, pp. 220-229 (Jackson, M. and Mantsch, H.H., Eds.) SPIE, San Jose, California, USA.
   

• The development and first use of Raman spectrometry in the non-invasive on-line determination of fermentation products.
  Shaw, A.D., Kaderbhai, N., Jones, A., Woodward, A.M., Goodacre, R., Rowland, J.J. and Kell, D.B. (1999) Non-invasive, on-line monitoring of the biotransformation by yeast of glucose to ethanol using dispersive Raman spectroscopy and chemometrics. Appl. Spectrosc. 53, 1419-1428.
  McGovern, A.C., Broadhurst, D., Taylor, J., Kaderbhai, N., Winson, M.K., Small, D.A., Rowland, J.J., Kell, D.B. & Goodacre, R. (2002) Monitoring of complex industrial bioprocesses for metabolite concentrations using modern spectroscopies and machine learning: application to gibberellic acid production. Biotechnology and Bioengineering 78, 527-538.
   

• The first demonstration that electrospray ionization mass spectrometry (ESI-MS) can be used for the reproducible characterisation of strains of intact bacteria.
  Goodacre, R., Heald, J.K. and Kell, D.B. (1999) Characterisation of intact microorganisms using electrospray ionization mass spectrometry. FEMS Microbiol. Lett. 176, 17-24.
  Vaidyanathan, S., Rowland, J.J., Kell, D.B. & Goodacre, R. (2001) Discrimination of aerobic endospore-forming bacteria via ESI-MS of whole cell suspensions.  Anal. Chem. 73, 4134-4144.
  Vaidyanathan, S., Kell, D.B. & Goodacre, R. (2002) Flow-injection ESI-MS of crude cell extracts for high-throughput bacterial identification.  J. Am. Soc. Mass Spectrom. 13, 118-128.
   

• The novel development of a probabilistic database for the identification of bacteria from amplified fragment length polymorphism patterns (AFLP; a genetic relatedness measure).
  Kassama, Y., Rooney, P.J. & Goodacre, R. (2002) A fluorescent AFLP probabilistic database for the identification of bacterial isolates from urinary tract infections.  J. Clin. Microbiol. 40, 2795–2800.
   

• The development of a novel non-destructive method based on infrared spectroscopy for the extremely rapid (60 s) detection of food spoilage in muscle foods.
  Ellis, D.I., Broadhurst, D., Kell, D.B., Rowland, J.J. & Goodacre, R. (2002) Rapid and quantitative detection of the microbial spoilage of meat using FT-IR spectroscopy and machine learning. Appl. Environ. Microbiol. 68, 2822-2828.
  Ellis, D.I., Broadhurst, D.I. & Goodacre, R. (2004) Rapid and quantitative detection of the microbial spoilage of beef by FT-IR spectroscopy and machine learning. Anal. Chim. Acta 514, 193-201.
   

• The development of MALDI-MS to detect high mass (> 20 kDa) proteins from bacterial cells.
  Vaidyanathan, S., Winder, C.L., Wade, S.C., Kell, D.B. & Goodacre, R. (2002) Sample preparation in matrix-assisted laser desorption/ionization mass spectrometry of whole bacterial cells and the detection of high mass (>20 kDa) proteins.  Rap. Comm. Mass Spectrom. 16, 1276-1286.
   

• The novel development of using genetic search to tune mass spectrometers.
  Vaidyanathan, S., Broadhurst, D.I., Kell D.B. & Goodacre, R. (2003) Explanatory optimisation of protein mass spectrometry via genetic search.  Anal. Chem. 75, 6679-6686.
   

• The novel development of UV resonance Raman spectroscopy with machine learning to characterise bacteria.
  López-Díez, E.C. & Goodacre, R. (2004) Characterisation of microorganisms using UV resonance Raman spectroscopy and chemometrics. Anal. Chem. 76, 585-591.
  Jarvis, R.M. & Goodacre, R. (2004) Ultra-violet resonance Raman spectroscopy for the rapid discrimination of urinary tract infection bacteria. FEMS Microbiol. Lett. 232, 127-132.
   

• The novel development of surface enhanced Raman spectroscopy with machine learning to characterise bacteria.
  Jarvis, R.M. & Goodacre, R. (2004) Rapid discrimination of bacteria using surface enhanced Raman spectroscopy. Anal. Chem. 76, 40-47.
  Jarvis, R.M., Brooker, A. & Goodacre, R. (2004) SERS for bacterial characterisation using a scanning electron microscope with a Raman spectroscopy interface.  Anal. Chem. 76, 5198-5202.
   

• The novel development of genetic algorithms with DFA and PLS for analysis of spectroscopic data.
  Jarvis, R.M. & Goodacre, R. (2004) Genetic algorithm optimisation for pre-processing and variable selection of spectroscopic data. Bioninformatics, in press.

Last updated 19 January 2005