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Items: 1 to 50 of 112

1.

Corruption of the Pearson correlation coefficient by measurement error and its estimation, bias, and correction under different error models.

Saccenti E, Hendriks MHWB, Smilde AK.

Sci Rep. 2020 Jan 16;10(1):438. doi: 10.1038/s41598-019-57247-4.

2.

Common and distinct variation in data fusion of designed experimental data.

Alinaghi M, Bertram HC, Brunse A, Smilde AK, Westerhuis JA.

Metabolomics. 2019 Dec 3;16(1):2. doi: 10.1007/s11306-019-1622-2.

3.

Repeatability and reproducibility of lipoprotein particle profile measurements in plasma samples by ultracentrifugation.

Monsonis-Centelles S, Hoefsloot HCJ, Engelsen SB, Smilde AK, Lind MV.

Clin Chem Lab Med. 2019 Dec 18;58(1):103-115. doi: 10.1515/cclm-2019-0729.

PMID:
31553695
4.

Principal component analysis of binary genomics data.

Song Y, Westerhuis JA, Aben N, Michaut M, Wessels LFA, Smilde AK.

Brief Bioinform. 2019 Jan 18;20(1):317-329. doi: 10.1093/bib/bbx119.

PMID:
30657888
5.

Data representations and -analyses of binary diary data in pursuit of stratifying children based on common childhood illnesses.

de Rooi J, Nørgaard SK, Rasmussen MA, Bønnelykke K, Bisgaard H, Smilde AK.

PLoS One. 2018 Nov 29;13(11):e0207177. doi: 10.1371/journal.pone.0207177. eCollection 2018.

6.

iTOP: inferring the topology of omics data.

Aben N, Westerhuis JA, Song Y, Kiers HAL, Michaut M, Smilde AK, Wessels LFA.

Bioinformatics. 2018 Sep 1;34(17):i988-i996. doi: 10.1093/bioinformatics/bty636.

7.

Dynamic elementary mode modelling of non-steady state flux data.

Folch-Fortuny A, Teusink B, Hoefsloot HCJ, Smilde AK, Ferrer A.

BMC Syst Biol. 2018 Jun 18;12(1):71. doi: 10.1186/s12918-018-0589-3.

8.

Group-wise ANOVA simultaneous component analysis for designed omics experiments.

Saccenti E, Smilde AK, Camacho J.

Metabolomics. 2018;14(6):73. doi: 10.1007/s11306-018-1369-1. Epub 2018 May 21.

9.

Fusing metabolomics data sets with heterogeneous measurement errors.

Waaijenborg S, Korobko O, Willems van Dijk K, Lips M, Hankemeier T, Wilderjans TF, Smilde AK, Westerhuis JA.

PLoS One. 2018 Apr 26;13(4):e0195939. doi: 10.1371/journal.pone.0195939. eCollection 2018.

10.

Erratum: Author Correction: Cellular and molecular synergy in AS01-adjuvanted vaccines results in an early IFNγ response promoting vaccine immunogenicity.

Coccia M, Collignon C, Hervé C, Chalon A, Welsby I, Detienne S, van Helden MJ, Dutta S, Genito CJ, Waters NC, Van Deun K, Smilde AK, van den Berg RA, Franco D, Bourguignon P, Morel S, Garçon N, Lambrecht BN, Goriely S, van der Most R, Didierlaurent AM.

NPJ Vaccines. 2018 Mar 21;3:13. doi: 10.1038/s41541-018-0047-7. eCollection 2018.

11.

Cellular and molecular synergy in AS01-adjuvanted vaccines results in an early IFNγ response promoting vaccine immunogenicity.

Coccia M, Collignon C, Hervé C, Chalon A, Welsby I, Detienne S, van Helden MJ, Dutta S, Genito CJ, Waters NC, Deun KV, Smilde AK, Berg RAVD, Franco D, Bourguignon P, Morel S, Garçon N, Lambrecht BN, Goriely S, Most RV, Didierlaurent AM.

NPJ Vaccines. 2017 Sep 8;2:25. doi: 10.1038/s41541-017-0027-3. eCollection 2017. Erratum in: NPJ Vaccines. 2018 Mar 21;3:13.

12.

Tutorial: Correction of shifts in single-stage LC-MS(/MS) data.

Mitra V, Smilde AK, Bischoff R, Horvatovich P.

Anal Chim Acta. 2018 Jan 25;999:37-53. doi: 10.1016/j.aca.2017.09.039. Epub 2017 Nov 2. Review.

13.

Toward Reliable Lipoprotein Particle Predictions from NMR Spectra of Human Blood: An Interlaboratory Ring Test.

Monsonis Centelles S, Hoefsloot HCJ, Khakimov B, Ebrahimi P, Lind MV, Kristensen M, de Roo N, Jacobs DM, van Duynhoven J, Cannet C, Fang F, Humpfer E, Schäfer H, Spraul M, Engelsen SB, Smilde AK.

Anal Chem. 2017 Aug 1;89(15):8004-8012. doi: 10.1021/acs.analchem.7b01329. Epub 2017 Jul 20.

14.

Acute Effects of Morning Light on Plasma Glucose and Triglycerides in Healthy Men and Men with Type 2 Diabetes.

Versteeg RI, Stenvers DJ, Visintainer D, Linnenbank A, Tanck MW, Zwanenburg G, Smilde AK, Fliers E, Kalsbeek A, Serlie MJ, la Fleur SE, Bisschop PH.

J Biol Rhythms. 2017 Apr;32(2):130-142. doi: 10.1177/0748730417693480. Epub 2017 Mar 20.

15.

Separating common from distinctive variation.

van der Kloet FM, Sebastián-León P, Conesa A, Smilde AK, Westerhuis JA.

BMC Bioinformatics. 2016 Jun 6;17 Suppl 5:195. doi: 10.1186/s12859-016-1037-2.

16.

Weight loss predictability by plasma metabolic signatures in adults with obesity and morbid obesity of the DiOGenes study.

Stroeve JH, Saccenti E, Bouwman J, Dane A, Strassburg K, Vervoort J, Hankemeier T, Astrup A, Smilde AK, van Ommen B, Saris WH.

Obesity (Silver Spring). 2016 Feb;24(2):379-88. doi: 10.1002/oby.21361.

17.

The Muscle Metabolome Differs between Healthy and Frail Older Adults.

Fazelzadeh P, Hangelbroek RW, Tieland M, de Groot LC, Verdijk LB, van Loon LJ, Smilde AK, Alves RD, Vervoort J, Müller M, van Duynhoven JP, Boekschoten MV.

J Proteome Res. 2016 Feb 5;15(2):499-509. doi: 10.1021/acs.jproteome.5b00840. Epub 2016 Jan 22.

PMID:
26732810
18.

Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes.

Kutzera J, Smilde AK, Wilderjans TF, Hoefsloot HC.

PLoS One. 2015 Oct 8;10(10):e0139704. doi: 10.1371/journal.pone.0139704. eCollection 2015.

19.

Scaling in ANOVA-simultaneous component analysis.

Timmerman ME, Hoefsloot HC, Smilde AK, Ceulemans E.

Metabolomics. 2015;11(5):1265-1276. Epub 2015 Feb 14.

20.

Validation and selection of ODE based systems biology models: how to arrive at more reliable decisions.

Hasdemir D, Hoefsloot HC, Smilde AK.

BMC Syst Biol. 2015 Jul 8;9:32. doi: 10.1186/s12918-015-0180-0.

21.

Using Petri nets for experimental design in a multi-organ elimination pathway.

Reshetova P, Smilde AK, Westerhuis JA, van Kampen AH.

Comput Biol Med. 2015 Aug;63:19-27. doi: 10.1016/j.compbiomed.2015.05.001. Epub 2015 May 12.

PMID:
26001852
22.

Not Just a Sum? Identifying Different Types of Interplay between Constituents in Combined Interventions.

Van Deun K, Thorrez L, van den Berg RA, Smilde AK, Van Mechelen I.

PLoS One. 2015 May 12;10(5):e0125334. doi: 10.1371/journal.pone.0125334. eCollection 2015.

23.

Strategies for individual phenotyping of linoleic and arachidonic acid metabolism using an oral glucose tolerance test.

Saccenti E, van Duynhoven J, Jacobs DM, Smilde AK, Hoefsloot HC.

PLoS One. 2015 Mar 18;10(3):e0119856. doi: 10.1371/journal.pone.0119856. eCollection 2015.

24.

MetDFBA: incorporating time-resolved metabolomics measurements into dynamic flux balance analysis.

Willemsen AM, Hendrickx DM, Hoefsloot HC, Hendriks MM, Wahl SA, Teusink B, Smilde AK, van Kampen AH.

Mol Biosyst. 2015 Jan;11(1):137-45. doi: 10.1039/c4mb00510d. Epub 2014 Oct 15.

PMID:
25315283
25.

Of monkeys and men: a metabolomic analysis of static and dynamic urinary metabolic phenotypes in two species.

Saccenti E, Tenori L, Verbruggen P, Timmerman ME, Bouwman J, van der Greef J, Luchinat C, Smilde AK.

PLoS One. 2014 Sep 15;9(9):e106077. doi: 10.1371/journal.pone.0106077. eCollection 2014.

26.

Nutrikinetic modeling reveals order of genistein phase II metabolites appearance in human plasma.

Smit S, Szymańska E, Kunz I, Gomez Roldan V, van Tilborg MW, Weber P, Prudence K, van der Kloet FM, van Duynhoven JP, Smilde AK, de Vos RC, Bendik I.

Mol Nutr Food Res. 2014 Nov;58(11):2111-21. doi: 10.1002/mnfr.201400325. Epub 2014 Aug 22.

PMID:
25045152
27.

Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data.

Reshetova P, Smilde AK, van Kampen AH, Westerhuis JA.

BMC Syst Biol. 2014;8 Suppl 2:S2. doi: 10.1186/1752-0509-8-S2-S2. Epub 2014 Mar 13. Review.

28.

Correlated measurement error hampers association network inference.

Kaduk M, Hoefsloot HC, Vis DJ, Reijmers T, van der Greef J, Smilde AK, Hendriks MM.

J Chromatogr B Analyt Technol Biomed Life Sci. 2014 Sep 1;966:93-9. doi: 10.1016/j.jchromb.2014.04.048. Epub 2014 May 2.

PMID:
24951433
29.

How informative is your kinetic model?: using resampling methods for model invalidation.

Hasdemir D, Hoefsloot HC, Westerhuis JA, Smilde AK.

BMC Syst Biol. 2014 May 22;8:61. doi: 10.1186/1752-0509-8-61.

30.

Network identification of hormonal regulation.

Vis DJ, Westerhuis JA, Hoefsloot HC, Roelfsema F, van der Greef J, Hendriks MM, Smilde AK.

PLoS One. 2014 May 22;9(5):e96284. doi: 10.1371/journal.pone.0096284. eCollection 2014.

31.

Identifying inhibitory compounds in lignocellulosic biomass hydrolysates using an exometabolomics approach.

Zha Y, Westerhuis JA, Muilwijk B, Overkamp KM, Nijmeijer BM, Coulier L, Smilde AK, Punt PJ.

BMC Biotechnol. 2014 Mar 21;14:22. doi: 10.1186/1472-6750-14-22.

32.

Inferring protein-protein interaction complexes from immunoprecipitation data.

Kutzera J, Hoefsloot HC, Malovannaya A, Smit AB, Van Mechelen I, Smilde AK.

BMC Res Notes. 2013 Nov 15;6:468. doi: 10.1186/1756-0500-6-468.

33.

Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: towards metabolomics diagnostics.

Szymańska E, Bouwman J, Strassburg K, Vervoort J, Kangas AJ, Soininen P, Ala-Korpela M, Westerhuis J, van Duynhoven JP, Mela DJ, Macdonald IA, Vreeken RJ, Smilde AK, Jacobs DM.

OMICS. 2012 Dec;16(12):652-67. doi: 10.1089/omi.2012.0062.

PMID:
23215804
34.

Assessing the metabolic effects of prednisolone in healthy volunteers using urine metabolic profiling.

Ellero-Simatos S, Szymańska E, Rullmann T, Dokter WH, Ramaker R, Berger R, van Iersel TM, Smilde AK, Hankemeier T, Alkema W.

Genome Med. 2012 Nov 30;4(11):94. doi: 10.1186/gm395. eCollection 2012.

35.

A critical assessment of feature selection methods for biomarker discovery in clinical proteomics.

Christin C, Hoefsloot HC, Smilde AK, Hoekman B, Suits F, Bischoff R, Horvatovich P.

Mol Cell Proteomics. 2013 Jan;12(1):263-76. doi: 10.1074/mcp.M112.022566. Epub 2012 Oct 31.

36.

A lipidomic analysis approach to evaluate the response to cholesterol-lowering food intake.

Szymańska E, van Dorsten FA, Troost J, Paliukhovich I, van Velzen EJ, Hendriks MM, Trautwein EA, van Duynhoven JP, Vreeken RJ, Smilde AK.

Metabolomics. 2012 Oct;8(5):894-906. Epub 2011 Dec 7.

37.

Topology of transcriptional regulatory networks: testing and improving.

Hasdemir D, Smits GJ, Westerhuis JA, Smilde AK.

PLoS One. 2012;7(7):e40082. doi: 10.1371/journal.pone.0040082. Epub 2012 Jul 23.

38.

Inferring differences in the distribution of reaction rates across conditions.

Hendrickx DM, Hoefsloot HC, Hendriks MM, Vis DJ, Canelas AB, Teusink B, Smilde AK.

Mol Biosyst. 2012 Sep;8(9):2415-23. Epub 2012 Jul 11.

PMID:
22782002
39.

DISCO-SCA and properly applied GSVD as swinging methods to find common and distinctive processes.

Van Deun K, Van Mechelen I, Thorrez L, Schouteden M, De Moor B, van der Werf MJ, De Lathauwer L, Smilde AK, Kiers HA.

PLoS One. 2012;7(5):e37840. doi: 10.1371/journal.pone.0037840. Epub 2012 May 31.

40.

Between Metabolite Relationships: an essential aspect of metabolic change.

Jansen JJ, Szymańska E, Hoefsloot HC, Jacobs DM, Strassburg K, Smilde AK.

Metabolomics. 2012 Jun;8(3):422-432. Epub 2011 May 24.

41.

Individual differences in metabolomics: individualised responses and between-metabolite relationships.

Jansen JJ, Szymańska E, Hoefsloot HC, Smilde AK.

Metabolomics. 2012 Jun;8(Suppl 1):94-104. Epub 2012 Mar 15.

42.

Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies.

Szymańska E, Saccenti E, Smilde AK, Westerhuis JA.

Metabolomics. 2012 Jun;8(Suppl 1):3-16. Epub 2011 Jul 8.

43.

Detecting regulatory mechanisms in endocrine time series measurements.

Vis DJ, Westerhuis JA, Hoefsloot HC, Roelfsema F, Hendriks MM, Smilde AK.

PLoS One. 2012;7(3):e32985. doi: 10.1371/journal.pone.0032985. Epub 2012 Mar 26.

44.

Global test for metabolic pathway differences between conditions.

Hendrickx DM, Hoefsloot HC, Hendriks MM, Canelas AB, Smilde AK.

Anal Chim Acta. 2012 Mar 16;719:8-15. doi: 10.1016/j.aca.2011.12.051. Epub 2012 Jan 4.

PMID:
22340525
45.

Generic framework for high-dimensional fixed-effects ANOVA.

Smilde AK, Timmerman ME, Hendriks MM, Jansen JJ, Hoefsloot HC.

Brief Bioinform. 2012 Sep;13(5):524-35. doi: 10.1093/bib/bbr071. Epub 2011 Dec 23. Review.

PMID:
22199378
46.

Beethoven's deafness and his three styles.

Saccenti E, Smilde AK, Saris WH.

BMJ. 2011 Dec 20;343:d7589. doi: 10.1136/bmj.d7589. No abstract available.

PMID:
22187391
47.

On the increase of predictive performance with high-level data fusion.

Doeswijk TG, Smilde AK, Hageman JA, Westerhuis JA, van Eeuwijk FA.

Anal Chim Acta. 2011 Oct 31;705(1-2):41-7. doi: 10.1016/j.aca.2011.03.025. Epub 2011 Mar 17.

PMID:
21962346
48.

Simplivariate models: uncovering the underlying biology in functional genomics data.

Saccenti E, Westerhuis JA, Smilde AK, van der Werf MJ, Hageman JA, Hendriks MM.

PLoS One. 2011;6(6):e20747. doi: 10.1371/journal.pone.0020747. Epub 2011 Jun 16.

49.

To aggregate or not to aggregate high-dimensional classifiers.

Xu CJ, Hoefsloot HC, Smilde AK.

BMC Bioinformatics. 2011 May 13;12:153. doi: 10.1186/1471-2105-12-153.

50.

New figures of merit for comprehensive functional genomics data: the metabolomics case.

Van Batenburg MF, Coulier L, van Eeuwijk F, Smilde AK, Westerhuis JA.

Anal Chem. 2011 May 1;83(9):3267-74. doi: 10.1021/ac102374c. Epub 2011 Mar 10.

PMID:
21391558

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