Fotograaf: onbekend

dhr. dr. J.A. (Johan) Westerhuis


  • Faculteit der Natuurwetenschappen, Wiskunde en Informatica
    Swammerdam Institute for Life Sciences
  • Bezoekadres
    Science Park A
    Science Park 904  Kamernummer: C2.206
  • Postadres:
    Postbus  94215
    1090 GE  Amsterdam
  • J.A.Westerhuis@uva.nl
    T: 0205256546

Introduction

Johan Westerhuis studied Analytical Chemistry/Chemometrics at the Rijks Hogeschool Groningen where he received his BSc degree in 1989. He then went to the Catholic University of Nijmegen to study Chemistry/Chemometrics in the group of Dr. L.M.C. Buydens, where he received his MSc degree in 1992. From 1992-1997 he worked towards a PhD at the University Centre for Pharmacy at the University of Groningen on Multivariate Statistical Modeling of the Pharmaceutical Process of Wet Granulation and Tableting.

From 1997 until 1998 he worked as a postdoctoral researcher at the Chemical Engineering Department of McMaster University , Hamilton, ON, Canada in the group of Dr. JF MacGregor. In October 1998 he joined the former Process Analysis & Chemometrics group (PAC), now the Biosystems Data Analysis group at the Universiteit van Amsterdam where he works as an assistent professor.

In 2010 he won the prestigious EAS Award for Outstanding Achievements in Chemometrics.

In 2012 he became an extraordinary professor at the BMI group of the North-West University in Potchefstroom, South Africa. Here he supervises projects in the metabolomics laboratory.

In 2013 he won two publication awards from the Metabolomics Society. 

Metabolomics Data Analysis

Functional genomics approaches are increasingly being used for the elucidation of complex biological questions with applications that range from human health via plants to microbial strain improvement . Metabolomics aims to measure the complete metabolomic response of an organism to the environmental conditions of interest. The main goal is to understand the cell in terms of metabolic and regulation networks, how are the different pathways connected and how are they regulated.

In our data analysis approach we aim at using prior information of the cells to improve the analysis results. Such an approach is called Grey Modelling . Grey models give a global overview of the cell with improved interpretability and they are able to reveal new molecular level information.

The development of data analysis tools to make such grey models is the key part of our research. How to incorporate prior knowledge on detailed kinetic models with different levels of confidence, how to include nonlinear metabolite/protein interactions and how to learn from the grey models ?
Recently, we developed Nutrikinetics , a new research field that studies what the body does to nutrients and their metabolites using specific kinetic models.
To learn about Nutrikinetics and How to deal with biological variation take a look at the following links:

Biosystems Data Analysis Master Course

Files needed for the master course on Biosystems Data Analysis can be found here.

Research Projects

  • Biologically Relevant Analysis of Metabolomics Data; Polina Reshetova
  • User-driven Development of Statistical Methods for Experimental Planning, Data Gathering, and Integrative Analysis of Next Generation Sequencing, Proteomics and Metabolomics data (STATegra, FP7 Health project)
  • Low level data fusion approaches to combine multiple functional genomics data sets of the same experiment for improved integration; Frans van der Kloet
  • Combining metabolomics, proteomics and genome sequencing data using dynamic flux models for experimental design purposes; Theo Reijmers
  • The metabolic consequences of acute alcohol abuse; Mari van Reenen (NWU, South Africa)

Selected Key Publications

  • Westerhuis JA, Hoefsloot HCJ, Smit S, Vis DJ, Smilde AK, van Velzen EJJ, van Duijnhoven JPM, van Dorsten FA, Assessment of PLSDA cross validation, Metabolomics, (2008), 4, 81-89.

 

  • Velzen EJJ, Westerhuis JA, van Duijnhoven JPM, van Dorsten FA, Grün C, Jacobs DM, Duchateau GSMJE, Vis D, Smilde AK, Phenotyping tea consumers by nutrikinetic analysis of polyphenol end metabolites, Journal of Proteome Research, (2009), 8, 3317-3330.

 

 

 

2017

2016

2015

  • Reshetova, P., Smilde, A. K., Westerhuis, J. A., & van Kampen, A. H. C. (2015). Using Petri nets for experimental design in a multi-organ elimination pathway. Computers in Biology and Medicine, 63, 19-27. DOI: 10.1016/j.compbiomed.2015.05.001  [details] 
  • Vis, D. J., Westerhuis, J. A., Jacobs, D. M., van Duynhoven, J. P. M., Wopereis, S., van Ommen, B., ... Smilde, A. K. (2015). Analyzing metabolomics-based challenge test. Metabolomics, 11(1), 50-63. DOI: 10.1007/s11306-014-0673-7  [details] 
  • Westerhuis, J. A., van Velzen, E. J. J., Jansen, J. J., Hoefsloot, H. C. J., & Smilde, A. K. (2015). Analysis of high-dimensional data from designed metabolomics studies. In M. Grootveld (Ed.), Metabolic profiling: disease and xenobiotics (pp. 117-136). (Issues in Toxicology; No. 21). Cambridge: Royal Society of Chemistry. DOI: 10.1039/9781849735162  [details] 

2014

2013

  • Smilde, A. K., Hendriks, M. M. W. B., Westerhuis, J., & Hoefsloot, H. C. J. (2013). Data Processing in Metabolomics. In M. Lämmerhofer, & W. Weckwerth (Eds.), Metabolomics in Practice: Successful Strategies to Generate and Analyze Metabolic Data (pp. 261- 284). Weinheim: Wiley-VCH. DOI: 10.1002/9783527655861.ch11  [details] 
  • González-Martínez, J. M., Westerhuis, J. A., & Ferrer, A. (2013). Using warping information for batch process monitoring and fault classification. Chemometrics and Intelligent Laboratory Systems, 127, 210-217. DOI: 10.1016/j.chemolab.2013.07.003  [details] 

2012

  • Hasdemir, D., Smits, G. J., Westerhuis, J. A., & Smilde, A. K. (2012). Topology of transcriptional regulatory networks: testing and improving. PLoS One, 7(7), [e40082]. [details] 
  • Jansen, J. J., & Westerhuis, J. A. (2012). Editorial-data analysis in metabolomics. Metabolomics, 8(Suppl 1), 1-2. DOI: 10.1007/s11306-012-0418-4  [details] 
  • Szymanska, E., Saccenti, E., Smilde, A. K., & Westerhuis, J. A. (2012). Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies. Metabolomics, 8(suppl. 1), 3-16. DOI: 10.1007/s11306-011-0330-3  [details] 
  • Szymańska, E., Bouwman, J., Strassburg, K., Vervoort, J., Kangas, A. J., Soininen, P., ... Jacobs, D. M. (2012). Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: towards metabolomics diagnostics. Omics, 16(12), 652-667. DOI: 10.1089/omi.2012.0062  [details] 
  • Vis, D. J., Westerhuis, J. A., Hoefsloot, H. C., Roelfsema, F., Hendriks, M. M. W. B., & Smilde, A. K. (2012). Detecting regulatory mechanisms in endocrine time series measurements. PLoS One, 7(3), [e32985]. DOI: 10.1371/journal.pone.0032985  [details] 
  • Yde, C. C., Westerhuis, J. A., Bertram, H. C., & Bach Knudsen, K. E. (2012). Application of NMR-based metabonomics suggests a relationship between betaine absorption and elevated creatine plasma concentrations in catheterised sows. British Journal of Nutrition, 107(11), 1603-1615. DOI: 10.1017/S0007114511004909  [details] 
  • van Duynhoven, J. P. M., van Velzen, E. J. J., Westerhuis, J. A., Foltz, M., Jacobs, D. M., & Smilde, A. K. (2012). Nutrikinetics: concept, technologies, applications, perspectives. Trends in Food Science & Technology, 26(1), 4-13. DOI: 10.1016/j.tifs.2012.01.004  [details] 

2011

  • Saccenti, E., Smilde, A. K., Westerhuis, J. A., & Hendriks, M. M. W. B. (2011). Tracy-Widom statistic for the largest eigenvalue of autoscaled real matrices. Journal of Chemometrics, 25(12), 644-652. DOI: 10.1002/cem.1411  [details] 
  • Saccenti, E., Westerhuis, J. A., Smilde, A. K., van der Werf, M. J., Hageman, J. A., & Hendriks, M. M. W. B. (2011). Simplivariate models: uncovering the underlying biology in functional genomics data. PLoS One, 6(6). DOI: 10.1371/journal.pone.0020747  [details] 
  • Zwanenburg, G., Hoefsloot, H. C. J., Westerhuis, J. A., Jansen, J. J., & Smilde, A. K. (2011). ANOVA-principal component analysis and ANOVA-simultaneous component analysis: a comparison. Journal of Chemometrics, 25(10), 561-567. DOI: 10.1002/cem.1400  [details] 
  • van Batenburg, M. F., Coulier, L., van Eeuwijk, F., Smilde, A. K., & Westerhuis, J. A. (2011). New figures of merit for comprehensive functional genomics data: the metabolomics case. Analytical Chemistry, 83(9), 3267-3274. DOI: 10.1021/ac102374c  [details] 
  • Doeswijk, T. G., Hageman, J. A., Westerhuis, J. A., Tikunov, Y., Bovy, A., & van Eeuwijk, F. A. (2011). Canonical correlation analysis of multiple sensory directed metabolomics data blocks reveals corresponding parts between data blocks. Chemometrics and Intelligent Laboratory Systems, 107(2), 371-376. DOI: 10.1016/j.chemolab.2011.05.010  [details] 
  • Doeswijk, T. G., Smilde, A. K., Hageman, J. A., Westerhuis, J. A., & van Eeuwijk, F. A. (2011). On the increase of predictive performance with high-level data fusion. Analytica Chimica Acta, 705(1-2), 41-47. DOI: 10.1016/j.aca.2011.03.025  [details] 
  • Gonzáles-Martínez, J. M., Ferrer, A., & Westerhuis, J. A. (2011). Real-time synchronization of batch trajectories for on-line multivariate statistical process control using Dynamic Time Warping. Chemometrics and Intelligent Laboratory Systems, 105(2), 195-206. DOI: 10.1016/j.chemolab.2011.01.003  [details] 
  • Hendriks, M. M. W. B., van Eeuwijk, F. A., Jellema, R. H., Westerhuis, J. A., Reijmers, T. H., Hoefsloot, H. C. J., & Smilde, A. K. (2011). Data-processing strategies for metabolomics studies. Trends in Analytical Chemistry, 30(10), 1685-1698. DOI: 10.1016/j.trac.2011.04.019  [details] 
  • van Duynhoven, J., Vaughan, E. E., Jacobs, D. M., Kemperman, R. A., van Velzen, E. J. J., Gross, G., ... van der Wiele, T. (2011). Metabolic fate of polyphenols in the human superorganism. Proceedings of the National Academy of Sciences of the United States of America, 108 Suppl, 4531-4538. DOI: 10.1073/pnas.1000098107  [details] 

2010

  • Smilde, A. K., Westerhuis, J. A., Hoefsloot, H. C. J., Bijlsma, S., Rubingh, C. M., Vis, D. J., ... van der Greef, J. (2010). Dynamic metabolomic data analysis: a tutorial review. Metabolomics, 6(1), 3-17. DOI: 10.1007/s11306-009-0191-1  [details] 
  • Vis, D. J., Westerhuis, J. A., Hoefsloot, H. C. J., Pijl, H., Roelfsema, F., van der Greef, J., & Smilde, A. K. (2010). Endocrine pulse identification using penalized methods and a minimum set of assumptions. American Journal of Physiology. Endocrinology and Metabolism, 298(2), E146-E155. DOI: 10.1152/ajpendo.00048.2009  [details] 
  • Westerhuis, J. A., van Velzen, E. J. J., Hoefsloot, H. C. J., & Smilde, A. K. (2010). Multivariate paired data analysis: multilevel PLSDA versus OPLSDA. Metabolomics, 6(1), 119-128. DOI: 10.1007/s11306-009-0185-z  [details] 
  • Zakrzewska, A., Boorsma, A., ter Beek, A., Hageman, J. A., Westerhuis, J. A., Hellingwerf, K. J., ... Smits, G. J. (2010). Comparative analysis of transcriptome and fitness profiles reveals general and condition-specific cellular functions involved in adaptation to environmental change in Saccharomyces cerevisiae. Omics, 14(5), 603-614. DOI: 10.1089/omi.2010.0049  [details] 

2009

  • Hoefsloot, H. C. J., Vis, D. J., Westerhuis, J. A., Smilde, A. K., & Jansen, J. J. (2009). Multiset data analysis: ANOVA simultaneous component analysis and related methods. In S. D. Brown, R. Tauler, & B. Walczak (Eds.), Comprehensive chemometrics: chemical and biochemical data analysis. - Vol. 2 (pp. 453-472). Amsterdam: Elsevier. DOI: 10.1016/B978-044452701-1.00054-5  [details] 
  • Verouden, M. P. H., Nootebaart, R. A., Westerhuis, J. A., van der Werf, M. J., Teusink, B., & Smilde, A. K. (2009). Multi-way analysis of flux distributions across multiple conditions. Journal of Chemometrics, 23(7-8), 406-420. DOI: 10.1002/cem.1238  [details] 
  • Verouden, M. P. H., Westerhuis, J. A., van der Werf, M. J., & Smilde, A. K. (2009). Exploring the analysis of structured metabolomics data. Chemometrics and Intelligent Laboratory Systems, 98(1), 88-96. DOI: 10.1016/j.chemolab.2009.05.004  [details] 
  • Westerhuis, J., van Velzen, E., Hoefsloot, H., & Smilde, A. (2009). Data analysis strategies in nutritional metabolomics. GIT Laboratory Journal Europe, 13(1-2), 17-19. [details] 
  • van Velzen, E. J. J., Westerhuis, J. A., van Duynhoven, J. P. M., van Dorsten, F. A., Grün, C. H., Jacobs, D. M., ... Smilde, A. K. (2009). Phenotyping tea consumers by nutrikinetic analysis of polyphenolic end-metabolites. Journal of Proteome Research, 8(7), 3317-3330. DOI: 10.1021/pr801071p  [details] 
  • van den Berg, R. A., Rubingh, C. M., Westerhuis, J. A., van der Werf, M. J., & Smilde, A. K. (2009). Metabolomics data exploration guided by prior knowledge. Analytica Chimica Acta, 651(2), 173-181. DOI: 10.1016/j.aca.2009.08.029  [details] 
  • Çakir, T., Hendriks, M. M. W. B., Westerhuis, J. A., & Smilde, A. K. (2009). Metabolic network discovery through reverse engineering of metabolome data. Metabolomics, 5(3), 318-329. DOI: 10.1007/s11306-009-0156-4  [details] 
  • van Duynhoven, J., van Velzen, E., Gross, G., van Dorsten, F., Jacobs, D., Bingham, M., ... Smilde, A. (2009). NMR-based metabonomics approaches for the assessment of the metabolic impact of dietary polyphenols on humans. Special Publication - Royal Society of Chemistry, 20-28. DOI: 10.1039/9781847559494-00020  [details] 

2008

  • Cruz, S. C., Rothenberg, G., Westerhuis, J. A., & Smilde, A. K. (2008). Estimating kinetic parameters of complex catalytic reactions using a curve resolution based method. Chemometrics and Intelligent Laboratory Systems, 91(2), 101-109. DOI: 10.1016/j.chemolab.2007.10.003  [details] 
  • Hageman, J. A., Hendriks, M. M. W. B., Westerhuis, J. A., van der Werf, M. J., Berger, R., & Smilde, A. K. (2008). Simplivariate models: Ideas and first examples. PLoS One, 3(9), e3259. DOI: 10.1371/journal.pone.0003259  [details] 
  • Hageman, J. A., van den Berg, R. A., Westerhuis, J. A., van der Werf, M. J., & Smilde, A. K. (2008). Genetic algorithm based two-mode clustering of metabolomics data. Metabolomics, 4(2), 141-149. DOI: 10.1007/s11306-008-0105-7  [details] 
  • Jansen, J. J., Bro, R., Hoefsloot, H. C. J., van den Berg, F. W. J., Westerhuis, J. A., & Smilde, A. K. (2008). PARAFASCA: ASCA combined with PARAFAC for the analysis of metabolic fingerprinting data. Journal of Chemometrics, 22(2), 114-121. DOI: 10.1002/cem.1105  [details] 
  • Smilde, A. K., Hoefsloot, H. C. J., & Westerhuis, J. A. (2008). The geometry of ASCA. Journal of Chemometrics, 22(8), 464-471. DOI: 10.1002/cem.1175  [details] 
  • Westerhuis, J. A., Hoefsloot, H. C. J., Smit, S., Vis, D. J., Smilde, A. K., van Velzen, E. J. J., ... van Dorsten, F. A. (2008). Assessment of PLSDA cross validation. Metabolomics, 4(1), 81-89. DOI: 10.1007/s11306-007-0099-6  [details] 
  • Westerhuis, J. A., van Velzen, E. J. J., Hoefsloot, H. C. J., & Smilde, A. K. (2008). Discriminant Q2 (DQ2) for improved discrimination in PLSDA models. Metabolomics, 4(4), 293-296. DOI: 10.1007/s11306-008-0126-2  [details] 
  • van Velzen, E. J. J., Westerhuis, J. A., van Duynhoven, J. P. M., van Dorsten, F. A., Hoefsloot, H. C. J., Jacobs, D. M., ... Smilde, A. K. (2008). Multilevel data analysis of a crossover designed human nutritional intervention study. Journal of Proteome Research, 7(10), 4483-4491. DOI: 10.1021/pr800145j  [details] 

Wetenschappelijke positie

  • Westerhuis, J. A. (2012-). Extraordinary Professor, North-West University, Potchefstroom, South Africa, Biosystems Data Analysis (SILS, FNWI).
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