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Results: 165
Number of items: 165
  • Open Access
    Smilde, A. K., Song, Y., Westerhuis, J. A., Kiers, H. A. L., Aben, N., & Wessels, L. F. A. (2021). Heterofusion: Fusing genomics data of different measurement scales. Journal of Chemometrics, 35(2), Article e3200. https://doi.org/10.1002/cem.3200
  • Open Access
    Zancarini, A., Westerhuis, J. A., Smilde, A. K., & Bouwmeester, H. J. (2021). Integration of omics data to unravel root microbiome recruitment. Current Opinion in Biotechnology, 70, 255-261. https://doi.org/10.1016/j.copbio.2021.06.016
  • Open Access
    Davarzani, N., Diez-Simon, C., Großmann, J. L., Jacobs, D. M., van Doorn, R., van den Berg, M. A., Smilde, A. K., Mumm, R., Hall, R. D., & Westerhuis, J. A. (2021). Systematic selection of competing metabolomics methods in a metabolite-sensory relationship study. Metabolomics, 17(9), Article 77. https://doi.org/10.1007/s11306-021-01821-3
  • Open Access
    Madssen, T. S., Giskeødegård, G. F., Smilde, A. K., & Westerhuis, J. A. (2021). Repeated measures ASCA+ for analysis of longitudinal intervention studies with multivariate outcome data. PLoS Computational Biology, 17(11), Article e1009585. https://doi.org/10.1371/journal.pcbi.1009585
  • Gomez-Cabrero, D., Tarazona, S., Ferreirós-Vidal, I., Ramirez, R. N., Company, C., Schmidt, A., Reijmers, T., Paul, V. v. S., Marabita, F., Rodríguez-Ubreva, J., Garcia-Gomez, A., Carroll, T., Cooper, L., Liang, Z., Dharmalingam, G., van der Kloet, F., Harms, A. C., Balzano-Nogueira, L., Lagani, V., … Conesa, A. (2020). Metadata record for: STATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse [Data set]. Figshare. https://doi.org/10.6084/m9.figshare.9773624.v2
  • Kuang, A., Erlund, I., Herder, C., Westerhuis, J. A., Tuomilehto, J., & Cornelis, M. C. (2020). Targeted proteomic response to coffee consumption. European Journal of Nutrition, 59(4), 1529-1539. https://doi.org/10.1007/s00394-019-02009-1
  • Westerhuis, J. A., van der Kloet, F., & Smilde, A. K. (2020). Data Fusion in Metabolomics. In R. Wehrens, & R. Salek (Eds.), Metabolomics: Practical Guide to Design and Analysis (pp. 157-176). (Chapman & Hall/CRC Mathematical and Computational Biology). CRC Press. https://doi.org/10.1201/9781315370583
  • Camacho, J., Smilde, A. K., Saccenti, E., & Westerhuis, J. A. (2020). All sparse PCA models are wrong, but some are useful. Part I: Computation of scores, residuals and explained variance. Chemometrics and Intelligent Laboratory Systems, 196, Article 103907. https://doi.org/10.1016/j.chemolab.2019.103907
  • Song, Y., Westerhuis, J. A., & Smilde, A. K. (2020). Logistic principal component analysis via non-convex singular value thresholding. Chemometrics and Intelligent Laboratory Systems, 204, Article 104089. https://doi.org/10.1016/j.chemolab.2020.104089
  • Open Access
    van der Kloet, F. M., Buurmans, J., Jonker, M. J., Smilde, A. K., & Westerhuis, J. A. (2020). Increased comparability between RNA-Seq and microarray data by utilization of gene sets. PLoS Computational Biology, 16(9), Article e1008295. https://doi.org/10.1371/journal.pcbi.1008295
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