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Results: 299
Number of items: 299
  • Open Access
    Zha, Y., Westerhuis, J. A., Muilwijk, B., Overkamp, K. M., Nijmeijer, B. M., Coulier, L., Smilde, A. K., & Punt, P. J. (2014). Identifying inhibitory compounds in lignocellulosic biomass hydrolysates using an exometabolomics approach. BMC Biotechnology, 14, 22. https://doi.org/10.1186/1472-6750-14-22
  • Open Access
    Bro, R., & Smilde, A. K. (2014). Principal component analysis. Analytical Methods, 6(9), 2812-2831. https://doi.org/10.1039/c3ay41907j
  • Open Access
    Hasdemir, D., Hoefsloot, H. C. J., Westerhuis, J. A., & Smilde, A. K. (2014). How informative is your kinetic model?: using resampling methods for model invalidation. BMC Systems Biology, 8, 61. https://doi.org/10.1186/1752-0509-8-61
  • Rubingh, C. M., Martens, H., van der Voet, H., & Smilde, A. K. (2013). The costs of complex model optimization. Chemometrics and Intelligent Laboratory Systems, 125, 139-146. https://doi.org/10.1016/j.chemolab.2013.04.004
  • van Deun, K., Smilde, A. K., Thorrez, L., Kiers, H. A. L., & van Mechelen, I. (2013). Identifying common and distinctive processes underlying multiset data. Chemometrics and Intelligent Laboratory Systems, 129, 40-51. https://doi.org/10.1016/j.chemolab.2013.07.005
  • Open Access
    Kutzera, J., Hoefsloot, H. C. J., Malovannaya, A., Smit, A. B., Van Mechelen, I., & Smilde, A. K. (2013). Inferring protein-protein interaction complexes from immunoprecipitation data. BMC Research Notes, 6, Article 468. https://doi.org/10.1186/1756-0500-6-468
  • 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). Wiley-VCH. https://doi.org/10.1002/9783527655861.ch11
  • Christin, C., Hoefsloot, H. C. J., Smilde, A. K., Hoekman, B., Suits, F., Bischoff, R., & Horvatovich, P. (2013). A critical assessment of feature selection methods for biomarker discovery in clinical proteomics. Molecular & Cellular Proteomics, 12(1), 263-276. https://doi.org/10.1074/mcp.M112.022566
  • Open Access
    Hendrickx, D. M. (2013). Network inference from time-resolved metabolomics data. [Thesis, fully internal, Universiteit van Amsterdam].
  • Hendrickx, D. M., Hoefsloot, H. C. J., Hendriks, M. M. W. B., Canelas, A. B., & Smilde, A. K. (2012). Global test for metabolic pathway differences between conditions. Analytica Chimica Acta, 719, 8-15. https://doi.org/10.1016/j.aca.2011.12.051
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