Prof. dr. A.K. (Age) Smilde
Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Swammerdam Institute for Life Sciences
Bezoekadres
- Science Park 904
- Kamernummer: C2.269
Postadres
- Postbus 1212
1000 BE Amsterdam
Contactgegevens
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Publicaties
- refereed (144)
- wetenschappelijk (1)
- vakpublicatie (1)
- overige (2)
- erkenning (15)
- supervised theses (1)
2022
Castro-Mejía, J. L., Khakimov, B., Aru, V., Lind, M. V., Garne, E., Paulová, P., Tavakkoli, E., Hansen, L. H., Smilde, A. K., Holm, L., Engelsen, S. B., & Nielsen, D. S. (2022). Gut Microbiome and Its Cofactors Are Linked to Lipoprotein Distribution Profiles. Microorganisms, 10(11), [2156]. https://doi.org/10.3390/microorganisms10112156 [details]- Khakimov, B., Hoefsloot, H. C. J., Mobaraki, N., Aru, V., Kristensen, M., Lind, M. V., Holm, L., Castro-Mejía, J. L., Nielsen, D. S., Jacobs, D. M., Smilde, A. K., & Engelsen, S. B. (2022). Human Blood Lipoprotein Predictions from 1H NMR Spectra: Protocol, Model Performances, and Cage of Covariance. Analytical Chemistry, 94(2), 628–636. https://doi.org/10.1101/2021.02.24.432509, https://doi.org/10.1021/acs.analchem.1c01654 [details]
- Kim, B., Westerhuis, J. A., Smilde, A. K., Floková, K., Suleiman, A. K. A., Kuramae, E. E., Bouwmeester, H. J., & Zancarini, A. (2022). Effect of strigolactones on recruitment of the rice root-associated microbiome. FEMS Microbiology Ecology, 98(2), [fiac010]. https://doi.org/10.1093/femsec/fiac010 [details]
- Leygeber, S., Grossmann, J. L., Díez-Simón, C., Karu, N., Dubbelman , A-C., Harms, A. C., Westerhuis, J. A., Jacobs, D. M., Lindenburg, P. W., Hendriks, M. M. W. B., Ammerlaan, B. C. H., van den Berg, M. A., van Doorn, R., Mumm, R., Hall, R. D., Smilde, A. K., & Hankemeier, T. (2022). Flavor Profiling Using Comprehensive Mass Spectrometry Analysis of Metabolites in Tomato Soups. Metabolites , 12(1194), [1194]. https://doi.org/10.3390/metabo12121194 [details]
- Li, L., Hoefsloot, H., de Graaf, A. A., Acar, E., & Smilde, A. K. (2022). Exploring dynamic metabolomics data with multiway data analysis: a simulation study. BMC Bioinformatics, 23(1), [31]. https://doi.org/10.1186/s12859-021-04550-5 [details]
- Smilde, A. K., Næs, T., & Liland, K. H. (2022). Multiblock Data Fusion in Statistics and Machine Learning: Applications in the Natural and Life Sciences. John Wiley & Sons. https://doi.org/10.1002/9781119600978 [details]
2021
- Camacho, J., Smilde, A. K., Saccenti, E., Westerhuis, J. A., & Bro, R. (2021). All sparse PCA models are wrong, but some are useful: Part II: Limitations and problems of deflation. Chemometrics and Intelligent Laboratory Systems, 208, [104212]. https://doi.org/10.1016/j.chemolab.2020.104212 [details]
- 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), [77]. https://doi.org/10.1007/s11306-021-01821-3 [details]
- 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), [e1009585]. https://doi.org/10.1371/journal.pcbi.1009585 [details]
- Næs, T., Romano, R., Tomic, O., Måge, I., Smilde, A., & Liland, K. H. (2021). Sequential and orthogonalized PLS (SO-PLS) regression for path analysis: Order of blocks and relations between effects. Journal of Chemometrics, 35(10), [e3243]. https://doi.org/10.1002/cem.3243 [details]
- Nørgaard, S. K., Linder-Steinlein, K., Eliasen, A. U., Stokholm, J., Chawes, B. L., Bønnelykke, K., Bisggard, H., Smilde, A. K., & Rasmussen, M. A. (2021). On using kernel integration by graphical LASSO to study partial correlations between heterogeneous data sets. Journal of Chemometrics, 35(10), [e3324]. https://doi.org/10.1002/cem.3324 [details]
- Skou, P. B., Hosseini, E., Ghasemi, J. B., Smilde, A. K., & Eskildsen, C. E. (2021). Orthogonality constrained inverse regression to improve model selectivity and analyte predictions from vibrational spectroscopic measurements. Analytica Chimica Acta, 1185, [339073]. https://doi.org/10.1016/j.aca.2021.339073 [details]
- 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), [e3200]. https://doi.org/10.1002/cem.3200 [details]
- Song, Y., Westerhuis, J. A., Aben, N., Wessels, L. F. A., Groenen, P. J. F., & Smilde, A. K. (2021). Generalized simultaneous component analysis of binary and quantitative data. Journal of Chemometrics, 35(3), [e3312]. https://doi.org/10.1002/cem.3312 [details]
- Tauler, R., Ruckebusch, C., & Smilde, A. (2021). TRICAP 2018 Angel Fire Resort, New Mexico. Journal of Chemometrics, 35(2), [e3313]. https://doi.org/10.1002/cem.3313 [details]
- Vitale, R., de Noord, O. E., Westerhuis, J. A., Smilde, A. K., & Ferrer, A. (2021). Divide et impera: How disentangling common and distinctive variability in multiset data analysis can aid industrial process troubleshooting and understanding. Journal of Chemometrics, 35(2), [e3266]. https://doi.org/10.1002/cem.3266 [details]
- 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 [details]
2020
- Alinaghi, M., Bertram, H. C., Brunse, A., Smilde, A. K., & Westerhuis, J. A. (2020). Common and distinct variation in data fusion of designed experimental data. Metabolomics, 16(1), [2]. https://doi.org/10.1007/s11306-019-1622-2 [details]
- 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, [103907]. https://doi.org/10.1016/j.chemolab.2019.103907 [details]
- Hasdemir, D., van den Berg, R. A., van Kampen, A., & Smilde, A. K. (2020). Modeling adaptive response profiles in a vaccine clinical trial. BMC Medical Research Methodology, 20, [191]. https://doi.org/10.1186/s12874-020-01070-3 [details]
- Kranenburg, R. F., Peroni, D., Affourtit, S., Westerhuis, J. A., Smilde, A. K., & van Asten, A. C. (2020). Revealing hidden information in GC–MS spectra from isomeric drugs: Chemometrics based identification from 15 eV and 70 eV EI mass spectra. Forensic Chemistry, 18, [100225]. https://doi.org/10.1016/j.forc.2020.100225 [details]
- Monsonis-Centelles, S., Hoefsloot, H. C. J., Engelsen, S. B., Smilde, A. K., & Lind, M. V. (2020). Repeatability and reproducibility of lipoprotein particle profile measurements in plasma samples by ultracentrifugation. Clinical chemistry and laboratory medicine, 58(1), 103-115. https://doi.org/10.1515/cclm-2019-0729 [details]
- Roeters, S. J., Sawall, M., Eskildsen, C. E., Panman, M. R., Tordai, G., Koeman, M., Neymeyr, K., Jansen, J., Smilde, A. K., & Woutersen, S. (2020). Unraveling VEALYL Amyloid Formation Using Advanced Vibrational Spectroscopy and Microscopy. Biophysical Journal, 119(1), 87-98. https://doi.org/10.1016/j.bpj.2020.05.026 [details]
- Saccenti, E., Hendriks, M. H. W. B., & Smilde, A. K. (2020). Corruption of the Pearson correlation coefficient by measurement error and its estimation, bias, and correction under different error models. Scientific Reports, 10, [438]. https://doi.org/10.1038/s41598-019-57247-4 [details]
- Smilde, A. K., & Hankemeier, T. (2020). Numerical Representations of Metabolic Systems. Analytical Chemistry, 92(20), 13614-13621. https://doi.org/10.1021/acs.analchem.9b05613 [details]
- 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, [104089]. https://doi.org/10.1016/j.chemolab.2020.104089 [details]
- Uh, H-W., Klarić, L., Ugrina, I., Lauc, G., Smilde, A. K., & Houwing-Duistermaat, J. J. (2020). Choosing proper normalization is essential for discovery of sparse glycan biomarkers. Omics, 16(3), 231-242. https://doi.org/10.1039/c9mo00174c [details]
- 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 [details]
- de Mot, L., Bechtold, V., Bol, V., Callegaro, A., Coccia, M., Essaghir, A., Hasdemir, D., Ulloa-Montoya, F., Siena, E., Smilde, A., van den Berg, R. A., Didierlaurent, A. M., Burny, W., & van der Most, R. G. (2020). Transcriptional profiles of adjuvanted hepatitis B vaccines display variable interindividual homogeneity but a shared core signature. Science translational medicine, 12(569), [eaay8618]. https://doi.org/10.1126/scitranslmed.aay8618 [details]
- 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), [e1008295]. https://doi.org/10.1371/journal.pcbi.1008295 [details]
2019
- Måge, I., Smilde, A. K., & van der Kloet, F. M. (2019). Performance of methods that separate common and distinct variation in multiple data blocks. Journal of Chemometrics, 33(1), [e3085]. https://doi.org/10.1002/cem.3085 [details]
- Song, Y., Westerhuis, J. A., Aben, N., Michaut, M., Wessels, L. F. A., & Smilde, A. K. (2019). Principal component analysis of binary genomics data. Briefings in Bioinformatics, 20(1), 317-329. https://doi.org/10.1093/bib/bbx119 [details]
2018
- Aben, N., Westerhuis, J. A., Song, Y., Kiers, H. A. L., Michaut, M., Smilde, A. K., & Wessels, L. F. A. (2018). iTOP: Inferring the topology of omics data. Bioinformatics, 34(17), i988-i996. https://doi.org/10.1093/bioinformatics/bty636 [details]
- Folch-Fortuny, A., Teusink, B., Hoefsloot, H. C. J., Smilde, A. K., & Ferrer, A. (2018). Dynamic elementary mode modelling of non-steady state flux data. BMC Systems Biology, 12, [71]. https://doi.org/10.1186/s12918-018-0589-3 [details]
- Mitra, V., Smilde, A. K., Bischoff, R., & Horvatovich, P. (2018). Tutorial: Correction of shifts in single-stage LC-MS(/MS) data. Analytica Chimica Acta, 999, 37-53. https://doi.org/10.1016/j.aca.2017.09.039 [details]
- Saccenti, E., Smilde, A. K., & Camacho, J. (2018). Group-wise ANOVA simultaneous component analysis for designed omics experiments. Metabolomics, 14(6), [73]. https://doi.org/10.1007/s11306-018-1369-1 [details]
- Waaijenborg, S., Korobko, O., Willems van Dijk, K., Lips, M., Hankemeier, T., Wilderjans, T. F., Smilde, A. K., & Westerhuis, J. A. (2018). Fusing metabolomics data sets with heterogeneous measurement errors. PLoS ONE, 13(4), [e0195939]. https://doi.org/10.1371/journal.pone.0195939 [details]
- de Rooi, J., Nørgaard, S. K., Rasmussen, M. A., Bønnelykke, K., Bisgaard, H., & Smilde, A. K. (2018). Data representations and -analyses of binary diary data in pursuit of stratifying children based on common childhood illnesses. PLoS ONE, 13(11), [e0207177]. https://doi.org/10.1371/journal.pone.0207177 [details]
2017
- Aru, V., Lam, C., Khakimov, B., Hoefsloot, H. C. J., Zwanenburg, G., Lind, M. V., Schäfer, H., van Duynhoven, J., Jacobs, D. M., Smilde, A. K., & Engelsen, S. B. (2017). Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis. Trends in Analytical Chemistry, 94, 210-219. https://doi.org/10.1016/j.trac.2017.07.009 [details]
- Coccia, M., Collignon, C., Hervé, C., Chalon, A., Welsby, I., Detienne, S., van Helden, M. J., Dutta, S., Genito, C. J., Waters, N. C., Van Deun, K., Smilde, A. K., van den Berg, R. A., Franco, D., Bourguignon, P., Morel, S., Garçon, N., Lambrecht, B. N., Goriely, S., ... Didierlaurent, A. M. (2017). Cellular and molecular synergy in AS01-adjuvanted vaccines results in an early IFNγ response promoting vaccine immunogenicity. Expert Review of Vaccines, 2, [25]. https://doi.org/10.1038/s41541-017-0027-3 [details]
- Monsonis Centelles, S., Hoefsloot, H. C. J., Khakimov, B., Ebrahimi, P., Lind, M. V., Kristensen, M., de Roo, N., Jacobs, D. M., van Duynhoven, J., Cannet, C., Fang, F., Humpfer, E., Schäfer, H., Spraul, M., Engelsen, S. B., & Smilde, A. K. (2017). Toward Reliable Lipoprotein Particle Predictions from NMR Spectra of Human Blood: An Interlaboratory Ring Test. Analytical Chemistry, 89(15), 8004-8012. https://doi.org/10.1021/acs.analchem.7b01329 [details]
- Versteeg, R. I., Stenvers, D. J., Visintainer, D., Linnenbank, A., Tanck, M. W., Zwanenburg, G., Smilde, A. K., Fliers, E., Kalsbeek, A., Serlie, M. J., la Fleur, S. E., & Bisschop, P. H. (2017). Acute Effects of Morning Light on Plasma Glucose and Triglycerides in Healthy Men and Men with Type 2 Diabetes. Journal of biological rhythms, 32(2), 130-142. https://doi.org/10.1177/0748730417693480 [details]
2016
- Fazelzadeh, P., Hangelbroek, R. W. J., Tieland, M., de Groot, C. P. G. M., Verdijk, L. B., van Loon, L. J. C., Smilde, A. K., Alves, R. D. A. M., Vervoort, J., Müller, M., van Duynhoven, J. P. M., & Boekschoten, M. V. (2016). The Muscle Metabolome Differs between Healthy and Frail Older Adults. Journal of Proteome Research, 15(2), 499-509. https://doi.org/10.1021/acs.jproteome.5b00840 [details]
- Gardlo, A., Smilde, A. K., Hron, K., Hrdá, M., Karlíková, R., Friedecký, D., & Adam, T. (2016). Normalization techniques for PARAFAC modeling of urine metabolomic data. Metabolomics, 12(7), [117]. https://doi.org/10.1007/s11306-016-1059-9 [details]
- Mitra, V., Govorukhina, N., Zwanenburg, G., Hoefsloot, H., Westra, I., Smilde, A., Reijmers, T., van der Zee, A. G. J., Suits, F., Bischoff, R., & Horvatovich, P. (2016). Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance: Simultaneous Component Analysis. Analytical Chemistry, 88(8), 4229-4238. https://doi.org/10.1021/acs.analchem.5b03483 [details]
- Stroeve, J. H. M., Saccenti, E., Bouwman, J., Dane, A., Strassburg, K., Vervoort, J., Hankemeier, T., Astrup, A., Smilde, A. K., van Ommen, B., & Saris, W. H. M. (2016). Weight loss predictability by plasma metabolic signatures in adults with obesity and morbid obesity of the DiOGenes study. Obesity, 24(2), 379-388. https://doi.org/10.1002/oby.21361 [details]
- van der Kloet, F. M., Sebastián-León, P., Conesa, A., Smilde, A. K., & Westerhuis, J. A. (2016). Separating common from distinctive variation. BMC Bioinformatics, 17(Suppl 5), [195]. https://doi.org/10.1186/s12859-016-1037-2 [details]
2015
- Hasdemir, D., Hoefsloot, H. C. J., & Smilde, A. K. (2015). Validation and selection of ODE based systems biology models: how to arrive at more reliable decisions. BMC Systems Biology, 9, 32. https://doi.org/10.1186/s12918-015-0180-0 [details]
- Horvatovich, P., Christin, C., Hoefsloot, H. C. J., Hoekman, B., Suits, F., Smilde, A. K., & Bischoff, R. (2015). Comparing the t-test, the Mann-Whitney-Wilcoxon test, nearest shrunken centroid, linear support vector machine - recursive features elimination, principal component discriminant analysis, and partial least squares discriminant analysis in biomarker discovery. In V. R. Preedy (Ed.), Biomarkers in Disease: Methods, Discoveries and Applications (Biomarkers in Disease: Methods, Discoveries and Applications). Springer.
- Kutzera, J., Smilde, A. K., Wilderjans, T. F., & Hoefsloot, H. C. J. (2015). Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes. PLoS ONE, 10(10), [0139704]. https://doi.org/10.1371/journal.pone.0139704 [details]
- 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. https://doi.org/10.1016/j.compbiomed.2015.05.001 [details]
- Saccenti, E., van Duynhoven, J., Jacobs, D. M., Smilde, A. K., & Hoefsloot, H. C. J. (2015). Strategies for individual phenotyping of linoleic and arachidonic acid metabolism using an oral glucose tolerance test. PLoS ONE, 10(3), e0119856. https://doi.org/10.1371/journal.pone.0119856 [details]
- Smilde, A. K., Timmerman, M. E., Saccenti, E., Jansen, J. J., & Hoefsloot, H. C. J. (2015). Covariances Simultaneous Component Analysis: a new method within a framework for modeling covariances. Journal of Chemometrics, 29(5), 277-288. https://doi.org/10.1002/cem.2707 [details]
- Timmerman, M. E., Hoefsloot, H. C. J., Smilde, A. K., & Ceulemans, E. (2015). Scaling in ANOVA-simultaneous component analysis. Metabolomics, 11(5), 1265-1276. https://doi.org/10.1007/s11306-015-0785-8 [details]
- Vis, D. J., Westerhuis, J. A., Jacobs, D. M., van Duynhoven, J. P. M., Wopereis, S., van Ommen, B., Hendriks, M. M. W. B., & Smilde, A. K. (2015). Analyzing metabolomics-based challenge test. Metabolomics, 11(1), 50-63. https://doi.org/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). Royal Society of Chemistry. https://doi.org/10.1039/9781849735162 [details]
- Willemsen, A. M., Hendrickx, D. M., Hoefsloot, H. C. J., Hendriks, M. M. W. B., Wahl, S. A., Teusink, B., Smilde, A. K., & van Kampen, A. H. C. (2015). MetDFBA: incorporating time-resolved metabolomics measurements into dynamic flux balance analysis. Molecular BioSystems, 11(1), 137-145. https://doi.org/10.1039/c4mb00510d [details]
- van Deun, K., Thorrez, L., van Berg, R. A., Smilde, A. K., & Van Mechelen, I. (2015). Not Just a Sum? Identifying Different Types of Interplay between Constituents in Combined Interventions. PLoS ONE, 10(5), [e0125334]. https://doi.org/10.1371/journal.pone.0125334 [details]
2014
- Bro, R., & Smilde, A. K. (2014). Principal component analysis. Analytical Methods, 6(9), 2812-2831. https://doi.org/10.1039/c3ay41907j [details]
- 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 [details]
- Kaduk, M., Hoefsloot, H. C. J., Vis, D. J., Reijmers, T., van der Greef, J., Smilde, A. K., & Hendriks, M. M. W. B. (2014). Correlated measurement error hampers association network inference. Journal of Chromatography B, 966, 93-99. https://doi.org/10.1016/j.jchromb2014.04.048 [details]
- Kvalheim, O. M., Arneberg, R., Bleie, O., Rajalahti, T., Smilde, A. K., & Westerhuis, J. A. (2014). Variable importance in latent variable regression models. Journal of Chemometrics, 28(8), 615-622. https://doi.org/10.1002/cem.2626 [details]
- Mihaleva, V. V., van Schalkwijk, D. B., de Graaf, A. A., van Duynhoven, J., van Dorsten, F. A., Vervoort, J., Smilde, A., Westerhuis, J. A., & Jacobs, D. M. (2014). A systematic approach to obtain validated Partial Least Square models for predicting lipoprotein subclasses from serum NMR spectra. Analytical Chemistry, 86(1), 543-550. https://doi.org/10.1021/ac402571z [details]
- Mitra, V., Smilde, A., Hoefsloot, H., Suits, F., Bischoff, R., & Horvatovich, P. (2014). Inversion of peak elution order prevents uniform time alignment of complex liquid-chromatography coupled to mass spectrometry datasets. Journal of Chromatography A, 1373, 61-72. https://doi.org/10.1016/j.chroma.2014.10.101 [details]
- Reshetova, P., Smilde, A. K., van Kampen, A. H. C., & Westerhuis, J. A. (2014). Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data. BMC Systems Biology, 8(suppl 2), S2. https://doi.org/10.1186/1752-0509-8-S2-S2 [details]
- Saccenti, E., Hoefsloot, H. C. J., Smilde, A. K., Westerhuis, J. A., & Hendriks, M. M. W. B. (2014). Reflections on univariate and multivariate analysis of metabolomics data. Metabolomics, 10(3), 361-374. https://doi.org/10.1007/s11306-013-0598-6 [details]
- Saccenti, E., Tenori, L., Verbruggen, P., Timmerman, M. E., Bouwman, J., van der Greef, J., Luchniat, C., & Smilde, A. K. (2014). Of monkeys and men: a metabolomic analysis of static and dynamic urinary metabolic phenotypes in two species. PLoS ONE, 9(9), e106077. https://doi.org/10.1371/journal.pone.0106077 [details]
- Smit, S., Szymańska, E., Kunz, I., Gomez Roldan, V., van Tilborg, M. W. E. M., Weber, P., Prudence, K., van der Kloet, F. M., van Duynhoven, J. P. M., Smilde, A. K., de Vos, R. C. H., & Bendik, I. (2014). Nutrikinetic modeling reveals order of genistein phase II metabolites appearance in human plasma. Molecular nutrition & food research, 58(11), 2111-2121. https://doi.org/10.1002/mnfr.201400325 [details]
- Vis, D. J., Hendriks, M. M. W. B., Sailer, M., Smilde, A. K., Daniel, H., & Westerhuis, J. A. (2014). A technical note on challenge tests in human volunteers for multidimensional phenotyping. Chemometrics and Intelligent Laboratory Systems, 136, 81-84. https://doi.org/10.1016/j.chemolab.2014.05.006 [details]
- Vis, D. J., Westerhuis, J. A., Hoefsloot, H. C. J., Roelfsema, F., van der Greef, J., Hendriks, M. M. W. B., & Smilde, A. K. (2014). Network identification of hormonal regulation. PLoS ONE, 9(5), e96284. https://doi.org/10.1371/journal.pone.0096284 [details]
- 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 [details]
- van Velzen, E. J. J., Westerhuis, J. A., Grün, C. H., Jacobs, D. M., Eilers, P. H. C., Mulder, T. P., Foltz, M., Garczarek, U., Kemperman, R., Vaughan, E. E., van Duynhoven, J. P. M., & Smilde, A. K. (2014). Population-based nutrikinetic modeling of polyphenol exposure. Metabolomics, 10(6), 1059-1073. https://doi.org/10.1007/s11306-014-0645-y [details]
2013
- 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 [details]
- 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, [468]. https://doi.org/10.1186/1756-0500-6-468 [details]
- 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 [details]
- 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 [details]
- 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 [details]
2012
- Ellero-Simatos, S., Szymańska, E., Rullmann, T., Dokter, W. H. A., Ramaker, R., Berger, R., van Iersel, T. M. P., Smilde, A. K., Hankemeier, T., & Alkema, W. (2012). Assessing the metabolic effects of prednisolone in healthy volunteers using urine metabolic profiling. Genome Medicine, 4(11), 94. https://doi.org/10.1186/gm395 [details]
- 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]
- 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 [details]
- Hendrickx, D. M., Hoefsloot, H. C. J., Hendriks, M. M. W. B., Vis, D. J., Canelas, A. B., Teusink, B., & Smilde, A. K. (2012). Inferring differences in the distribution of reaction rates across conditions. Molecular BioSystems, 8(9), 2415-2423. https://doi.org/10.1039/c2mb25015b [details]
- Jansen, J. J., Szymanska, E., Hoefsloot, H. C. J., & Smilde, A. K. (2012). Individual differences in metabolomics: individualised responses and between-metabolite relationships. Metabolomics, 8(Suppl 1), 94-104. https://doi.org/10.1007/s11306-012-0414-8 [details]
- Jansen, J. J., Szymanska, E., Hoefsloot, H. C. J., Jacobs, D. M., Strassburg, K., & Smilde, A. K. (2012). Between Metabolite Relationships: an essential aspect of metabolic change. Metabolomics, 8, 422-432. https://doi.org/10.1007/s11306-011-0316-1 [details]
- Smilde, A. K., Timmerman, M. E., Hendriks, M. M. W. B., Jansen, J. J., & Hoefsloot, H. C. J. (2012). Generic framework for high-dimensional fixed-effects ANOVA. Briefings in Bioinformatics, 13(5), 524-535. https://doi.org/10.1093/bib/bbr071 [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. https://doi.org/10.1007/s11306-011-0330-3 [details]
- Szymańska, E., Bouwman, J., Strassburg, K., Vervoort, J., Kangas, A. J., Soininen, P., Ala-Korpela, M., Westerhuis, J., van Duynhoven, J. P. M., Mela, D. J., Macdonald, I. A., Vreeken, R. J., Smilde, A. K., & 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. https://doi.org/10.1089/omi.2012.0062 [details]
- Szymańska, E., van Dorsten, F. A., Troost, J., Paliukhovich, I., van Velzen, E. J. J., Hendriks, M. M. W. B., Trautwein, E. A., van Duynhoven, J. P. M., Vreeken, R. J., & Smilde, A. K. (2012). A lipidomic analysis approach to evaluate the response to cholesterol-lowering food intake. Metabolomics, 8(5), 894-906. https://doi.org/10.1007/s11306-011-0384-2 [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]. https://doi.org/10.1371/journal.pone.0032985 [details]
- Wopereis, S., Radonjic, M., Rubingh, C., van Erk, M., Smilde, A., van Duyvenvoorde, W., Cnubben, N., Kooistra, T., van Ommen, B., & Kleemann, R. (2012). Identification of prognostic and diagnostic biomarkers of glucose intolerance in ApoE3Leiden mice. Physiological Genomics, 44(5), 293-304. https://doi.org/10.1152/physiolgenomics.00072.2011 [details]
- van Deun, K., van Mechelen, I., Thorrez, L., Schouteden, M., de Moor, B., van der Werf, M. J., de Lathauwer, L., Smilde, A. K., & Kiers, H. A. L. (2012). DISCO-SCA and properly applied GSVD as swinging methods to find common and distinctive processes. PLoS ONE, 7(5), e37840. https://doi.org/10.1371/journal.pone.0037840 [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. https://doi.org/10.1016/j.tifs.2012.01.004 [details]
2011
- 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. https://doi.org/10.1016/j.aca.2011.03.025 [details]
- Hendrickx, D. M., Hendriks, M. M. W. B., Eilers, P. H. C., Smilde, A. K., & Hoefsloot, H. C. J. (2011). Reverse engineering of metabolic networks, a critical assessment. Molecular BioSystems, 7(2), 511-520. https://doi.org/10.1039/c0mb00083c [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. https://doi.org/10.1016/j.trac.2011.04.019 [details]
- Rubingh, C. M., van Erk, M. J., Wopereis, S., van Vliet, T., Verheij, E. R., Cnubben, N. H. P., van Ommen, B., van der Greef, J., Hendriks, H. F. J., & Smilde, A. K. (2011). Discovery of subtle effects in a human intervention trial through multilevel modeling. Chemometrics and Intelligent Laboratory Systems, 106(1), 108-114. https://doi.org/10.1016/j.chemolab.2010.06.003 [details]
- Saccenti, E., Smilde, A. K., & Saris, W. H. M. (2011). Beethoven's deafness and his three styles. BMJ : British medical journal, 343, d7589. [d7589]. https://doi.org/10.1136/bmj.d7589 [details]
- 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. https://doi.org/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). https://doi.org/10.1371/journal.pone.0020747 [details]
- Smilde, A., & Tauler, R. (2011). Multiway and multiset data analysis. Chemometrics and Intelligent Laboratory Systems, 106, 1-1. https://doi.org/10.1016/j.chemolab.2010.09.009 [details]
- Xu, C. J., Hoefsloot, H. C. J., & Smilde, A. K. (2011). To aggregate or not to aggregate high-dimensional classifiers. BMC Bioinformatics, 12. https://doi.org/10.1186/1471-2105-12-153 [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. https://doi.org/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. https://doi.org/10.1021/ac102374c [details]
- van Duynhoven, J., Vaughan, E. E., Jacobs, D. M., Kemperman, R. A., van Velzen, E. J. J., Gross, G., Roger, L. C., Possemiers, S., Smilde, A. K., Doré, J., Westerhuis, J. A., & 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. https://doi.org/10.1073/pnas.1000098107 [details]
- van Mechelen, I., & Smilde, A. K. (2011). Comparability problems in the analysis of multiway data. Chemometrics and Intelligent Laboratory Systems, 106(1), 2-11. https://doi.org/10.1016/j.chemolab.2010.08.006 [details]
2010
- Christin, C., Hoefsloot, H. C. J., Smilde, A. K., Suits, F., Bischoff, R., & Horvatovich, P. L. (2010). Time alignment algorithms based on selected mass traces for complex LC-MS data. Journal of Proteome Research, 9(3), 1483-1495. https://doi.org/10.1021/pr9010124 [details]
- Jansen, J. J., Smit, S., Hoefsloot, H. C. J., & Smilde, A. K. (2010). The photographer and the greenhouse: how to analyse plant metabolomics data. Phytochemical Analysis, 21(1), 48-60. https://doi.org/10.1002/pca.1181 [details]
- Smilde, A. K., Westerhuis, J. A., Hoefsloot, H. C. J., Bijlsma, S., Rubingh, C. M., Vis, D. J., Jellema, R. H., Pijl, H., Roelfsema, F., & van der Greef, J. (2010). Dynamic metabolomic data analysis: a tutorial review. Metabolomics, 6(1), 3-17. https://doi.org/10.1007/s11306-009-0191-1 [details]
- Stanimirovic, O., Hoefsloot, H. C. J., & Smilde, A. K. (2010). Optimal measurement design for monitoring batch processes. AIChE Journal, 56(3), 837-840. https://doi.org/10.1002/aic.11968 [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. https://doi.org/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. https://doi.org/10.1007/s11306-009-0185-z [details]
- Xu, C. J., Hoefsloot, H. C. J., Dijkstra, M., Havenga, K., Roelofsen, H., Vonk, R. J., & Smilde, A. K. (2010). Computational modeling of the human serum proteome response to colon resection surgery. Analytica Chimica Acta, 661(1), 20-27. https://doi.org/10.1016/j.aca.2009.12.003 [details]
- van Erk, M. J., Wopereis, S., Rubingh, C., van Vliet, T., Verheij, E., Cnubben, N. H. P., Pedersen, T. L., Newman, J. W., Smilde, A. K., van der Greef, J., Hendriks, H. F. J., & van Ommen, B. (2010). Insight in modulation of inflammation in response to diclofenac intervention: a human intervention study. BMC Medical Genomics, 3, 5. https://doi.org/10.1186/1755-8794-3-5 [details]
- van Mechelen, I., & Smilde, A. K. (2010). A generic linked-mode decomposition model for data fusion. Chemometrics and Intelligent Laboratory Systems, 104(1), 83-94. https://doi.org/10.1016/j.chemolab.2010.04.012 [details]
2009
- Boot, R. G., van Breemen, M. J., Wegdam, W., Sprenger, R. R., de Jong, S., Speijer, D., Hollak, C. E. M., van Dussen, L., Hoefsloot, H. C. J., Smilde, A. K., de Koster, C. G., Vissers, J. P. C., & Aerts, J. M. F. G. (2009). Gaucher disease: a model disorder for biomarker discovery. Expert Review of Proteomics, 6(4), 411-419. https://doi.org/10.1586/epr.09.54 [details]
- Braaksma, M., Smilde, A. K., van der Werf, M. J., & Punt, P. J. (2009). The effect of environmental conditions on extracellular protease activity in controlled fermentations of Aspergillus niger. Microbiology - SGM, 155(10), 3430-3439. https://doi.org/10.1099/mic.0.031062-0 [details]
- 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). Elsevier. https://doi.org/10.1016/B978-044452701-1.00054-5 [details]
- Jansen, J. J., van Dam, N. M., Hoefsloot, H. C. J., & Smilde, A. K. (2009). Crossfit analysis: a novel method to characterize the dynamics of induced plant responses. BMC Bioinformatics, 10, 425. https://doi.org/10.1186/1471-2105-10-425 [details]
- Smilde, A. K., Kiers, H. A. L., Bijlsma, S., Rubingh, C. M., & van Erk, M. J. (2009). Matrix correlations for high-dimensional data: the modified RV-coefficient. Bioinformatics, 25(3), 401-405. https://doi.org/10.1093/bioinformatics/btn634 [details]
- Smilde, A. K., van der Werf, M. J., Schaller, J. P., & Kistemaker, C. (2009). Characterizing the precision of mass-spectrometry-based metabolic profiling platforms. Analyst, 134(11), 2281-2285. https://doi.org/10.1039/b902242b [details]
- Thissen, U., Wopereis, S., van Berg, S. A. A., Bobeldijk, I., Kleemann, R., Kooistra, T., van Dijk, K. W., van Ommen, B., & Smilde, A. K. (2009). Improving the analysis of designed studies by combining statistical modelling with study design information. BMC Bioinformatics, 10, 52. https://doi.org/10.1186/1471-2105-10-52 [details]
- Timmerman, M. E., Kiers, H. A. L., Smilde, A. K., Ceulemans, E., & Stouten, J. (2009). Bootstrap confidence intervals in multi-level simultaneous component analysis. British Journal of Mathematical & Statistical Psychology, 62(2), 299-318. https://doi.org/10.1348/000711007X265894 [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. https://doi.org/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. https://doi.org/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. http://www.laboratory-journal.com/science/lebensmittel/data-analysis-strategies-nutritional-metabolomics [details]
- Wopereis, S., Rubingh, C. M., van Erk, M. J., Verheij, E. R., van Vliet, T., Cnubben, N. H. P., Smilde, A. K., van der Greef, J., van Ommen, B., & Hendriks, H. F. J. (2009). Metabolic profiling of the response to an oral glucose tolerance test detects subtle metabolic changes. PLoS ONE, 4(2), e4525. https://doi.org/10.1371/journal.pone.0004525 [details]
- van Deun, K., Smilde, A. K., van der Werf, M. J., Kiers, H. A. L., & van Mechelen, I. (2009). A structured overview of simultaneous component based data integration. BMC Bioinformatics, 10, 246. https://doi.org/10.1186/1471-2105-10-246 [details]
- van Duynhoven, J., van Velzen, E., Gross, G., van Dorsten, F., Jacobs, D., Bingham, M., Draijer, R., Mulder, T., Koning, T., Vaughan, E., van der Wiele, T., Westerhuis, J., & 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. https://doi.org/10.1039/9781847559494-00020 [details]
- van Velzen, E. J. J., Westerhuis, J. A., van Duynhoven, J. P. M., van Dorsten, F. A., Grün, C. H., Jacobs, D. M., Duchateau, G. S. M. J. E., Vis, D. J., & Smilde, A. K. (2009). Phenotyping tea consumers by nutrikinetic analysis of polyphenolic end-metabolites. Journal of Proteome Research, 8(7), 3317-3330. https://doi.org/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. https://doi.org/10.1016/j.aca.2009.08.029 [details]
- van den Berg, R. A., van Mechelen, I., Wilderjans, T. F., van Deun, K., Kiers, H. A. L., & Smilde, A. K. (2009). Integrating functional genomics data using maximum likelihood based simultaneous component analysis. BMC Bioinformatics, 10, 340. https://doi.org/10.1186/1471-2105-10-340 [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. https://doi.org/10.1007/s11306-009-0156-4 [details]
2008
- Aerts, J. M., van Breemen, M. J., Bussink, A. P., Ghauharali, K., Sprenger, R., Boot, R. G., Groener, J. E., Hollak, C. E., Maas, M., Smit, S., Hoefsloot, H. C., Smilde, A. K., Vissers, J. P. C., de Jong, S., Speijer, D., & de Koster, C. G. (2008). Biomarkers for lysosomal storage disorders: Identification and application as exemplified by chitotriosidase in Gaucher disease. Acta Paediatrica, 97(s457), 7-14. https://doi.org/10.1111/j.1651-2227.2007.00641.x [details]
- Bro, R., Kjeldahl, K., Smilde, A. K., & Kiers, H. A. L. (2008). Cross-validation of component models: A critical look at current methods. Analytical and Bioanalytical Chemistry, 390(5), 1241-1251. https://doi.org/10.1007/s00216-007-1790-1 [details]
- Christin, C., Smilde, A. K., Hoefsloot, H. C. J., Suits, F., Bischoff, R., & Horvatovich, P. L. (2008). Optimized time alignment algorithm for LC-MS data: Correlation optimized warping using component detection algorithm-selected mass chromatograms. Analytical Chemistry, 80(18), 7012-7021. https://doi.org/10.1021/ac800920h [details]
- 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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/10.1002/cem.1175 [details]
- Smit, S., Hoefsloot, H. C. J., & Smilde, A. K. (2008). Statistical data processing in clinical proteomics. Journal of Chromatography B, 866(1-2), 77-88. https://doi.org/10.1016/j.jchromb.2007.10.042 [details]
- Stanimirovic, O., Hoefsloot, H. C. J., de Bokx, P. K., & Smilde, A. K. (2008). Variable selection methods as a tool to find sensor locations for distributed parameter systems. Industrial & Engineering Chemistry Research, 47(4), 1184-1191. https://doi.org/10.1021/ie070946i [details]
- Westerhuis, J. A., Hoefsloot, H. C. J., Smit, S., Vis, D. J., Smilde, A. K., van Velzen, E. J. J., van Duijnhoven, J. P. M., & van Dorsten, F. A. (2008). Assessment of PLSDA cross validation. Metabolomics, 4(1), 81-89. https://doi.org/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. https://doi.org/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., Smit, S., Draijer, R., Kroner, C. I., & Smilde, A. K. (2008). Multilevel data analysis of a crossover designed human nutritional intervention study. Journal of Proteome Research, 7(10), 4483-4491. https://doi.org/10.1021/pr800145j [details]
2019
- Aru, V., Lam, C., Khakimov, B., Hoefsloot, H. C. J., Zwanenburg, G., Lind, M. V., Schäfer, H., van Duynhoven, J., Jacobs, D. M., Smilde, A. K., & Engelsen, S. B. (2019). Corrigendum to “Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis” [Trends Anal Chem 94 (2017) 210–219](S0165993617301024)(10.1016/j.trac.2017.07.009)). TrAC - Trends in Analytical Chemistry, 119, [115631]. https://doi.org/10.1016/j.trac.2019.115631
2008
- Hoefsloot, H. C. J., Smit, S., & Smilde, A. K. (2008). A classification model for the Leiden proteomics competition. Statistical Applications in Genetics and Molecular Biology, 7(2), 8. http://www.bepress.com/sagmb/vol7/iss2/art8 [details]
2014
- Coccia, M., Herve, C., Collignon, C., Van Deun, K., van den Berg, R. A., Van Mechelen, I., Smilde, A. K., Morel, S., Garcon, N., van der Most, R., Van Mechelen, M., & Didierlaurent, A. M. (2014). Early NK cell activation as a result of MPL and QS-21 combination controls the adjuvant effect induced by the human Adjuvant System AS01. Immunology, 143(S2), 61. https://doi.org/10.1111/imm.12405 [details]
2011
- Saccenti, E. (Author), & Smilde, A. K. (Author). (2011). Beethoven's deafness and his three styles. Digital or Visual Products, British Medical Journal. http://www.youtube.com/embed/W1HyszALJZE
Lidmaatschap / relevante positie
- Smilde, A. K. (2016-). Member of the Scientific Advisory Board of the CALM Consortium, Danish Research Foundation CALM project.
- Smilde, A. K. (2016-). Member of the Scientific Advisory Board, ASK Consortium .
- Smilde, A. K. (2016-). Member of the Scientific Advisory Board BIOPROD II Consortium, Copenhagen, Denmark, BIOPROD II Consortium Copenhagen Denmark.
- Smilde, A. K. (2016-). Member of the Scientific Advisory Board of the BIOPROD II Consortium, Copenhagen, Denmark, .
- Smilde, A. K. (2016-). Member of the Scientific Advisory Board of the ASK Consortium, .
- Smilde, A. K. (2016-). Member of the Scientific Advisory Board of the Consortium MIMOmics, European Union, Brussels, EU project Mimomics.
- Smilde, A. K. (2014-). Scientific Advisory Board of Danish Research Foundation BIOPROD2 project, Danish Research Foundation.
- Smilde, A. K. (2014-). Part-time professor, Kopenhagen University (Faculty of Science, Faculty of Health and Medical Sciences).
- Smilde, A. K. (2014-). Board member, the Netherlands Metabolomics Centre.
- Smilde, A. K. (2014-2017). Member of the Scientific Advisory Board of the CALM Consortium, Danish Research Foundation CALM project.
- Smilde, A. K. (2014-2017). Principal Investigator, AMC.
- Smilde, A. K. (2013-2017). Scientific Advisory Board of the Consortium MIMOmics, European Union, Brussels.
- Smilde, A. K. (2013-). Part-time professor at the Department of Health Science, .
- Smilde, A. K. (2013-). Part-time professor at the Department of Food Science, .
Spreker
- Smilde, A. K. (invited speaker) (19-4-2016). Critical Issues in Metabolomics Data Analysis, BioSB Symposium , Lunteren.
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Nevenwerkzaamheden
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University of Copenhagen
Deeltijd hoogleraar Computational Systems Biology -
Simula (Oslo, Noorwegen)
Research Professor Machine Learning for the Life Sciences
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University of Copenhagen
Castro-Mejía, J. L., Khakimov, B., Aru, V., Lind, M. V., Garne, E., Paulová, P., Tavakkoli, E., Hansen, L. H., Smilde, A. K., Holm, L., Engelsen, S. B., & Nielsen, D. S. (2022). Gut Microbiome and Its Cofactors Are Linked to Lipoprotein Distribution Profiles. Microorganisms, 10(11), [2156].