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Items: 1 to 50 of 66

1.

Actions of metformin and statins on lipid and glucose metabolism and possible benefit of combination therapy.

van Stee MF, de Graaf AA, Groen AK.

Cardiovasc Diabetol. 2018 Jun 30;17(1):94. doi: 10.1186/s12933-018-0738-4. Review.

2.

Feed-forward neural network model for hunger and satiety related VAS score prediction.

Krishnan S, Hendriks HF, Hartvigsen ML, de Graaf AA.

Theor Biol Med Model. 2016 Jul 7;13(1):17. doi: 10.1186/s12976-016-0043-4.

3.

The effect of plant sterols and different low doses of omega-3 fatty acids from fish oil on lipoprotein subclasses.

Jacobs DM, Mihaleva VV, van Schalkwijk DB, de Graaf AA, Vervoort J, van Dorsten FA, Ras RT, Demonty I, Trautwein EA, van Duynhoven J.

Mol Nutr Food Res. 2015 Sep;59(9):1745-57. doi: 10.1002/mnfr.201500152. Epub 2015 Jun 22.

PMID:
26019023
4.

Predicting individual responses to pravastatin using a physiologically based kinetic model for plasma cholesterol concentrations.

van de Pas NC, Rullmann JA, Woutersen RA, van Ommen B, Rietjens IM, de Graaf AA.

J Pharmacokinet Pharmacodyn. 2014 Aug;41(4):351-62. doi: 10.1007/s10928-014-9369-x. Epub 2014 Aug 9.

PMID:
25106950
5.

Dietary medium chain fatty acid supplementation leads to reduced VLDL lipolysis and uptake rates in comparison to linoleic acid supplementation.

van Schalkwijk DB, Pasman WJ, Hendriks HF, Verheij ER, Rubingh CM, van Bochove K, Vaes WH, Adiels M, Freidig AP, de Graaf AA.

PLoS One. 2014 Jul 21;9(7):e100376. doi: 10.1371/journal.pone.0100376. eCollection 2014.

6.

A new flexible plug and play scheme for modeling, simulating, and predicting gastric emptying.

Krishnan S, van Avesaat M, Troost FJ, Hendriks HF, de Graaf AA.

Theor Biol Med Model. 2014 Jun 10;11:28. doi: 10.1186/1742-4682-11-28.

7.

Lipoprotein metabolism indicators improve cardiovascular risk prediction.

van Schalkwijk DB, de Graaf AA, Tsivtsivadze E, Parnell LD, van der Werff-van der Vat BJ, van Ommen B, van der Greef J, Ordovás JM.

PLoS One. 2014 Mar 25;9(3):e92840. doi: 10.1371/journal.pone.0092840. eCollection 2014.

8.

A systematic approach to obtain validated partial least square models for predicting lipoprotein subclasses from serum NMR spectra.

Mihaleva VV, van Schalkwijk DB, de Graaf AA, van Duynhoven J, van Dorsten FA, Vervoort J, Smilde A, Westerhuis JA, Jacobs DM.

Anal Chem. 2014 Jan 7;86(1):543-50. doi: 10.1021/ac402571z. Epub 2013 Dec 18.

PMID:
24319989
9.

A physiologically based in silico kinetic model predicting plasma cholesterol concentrations in humans.

van de Pas NC, Woutersen RA, van Ommen B, Rietjens IM, de Graaf AA.

J Lipid Res. 2012 Dec;53(12):2734-46. doi: 10.1194/jlr.M031930. Epub 2012 Sep 29.

10.

Clustering by plasma lipoprotein profile reveals two distinct subgroups with positive lipid response to fenofibrate therapy.

van Bochove K, van Schalkwijk DB, Parnell LD, Lai CQ, Ordovás JM, de Graaf AA, van Ommen B, Arnett DK.

PLoS One. 2012;7(6):e38072. doi: 10.1371/journal.pone.0038072. Epub 2012 Jun 12.

11.

Diagnostic markers based on a computational model of lipoprotein metabolism.

van Schalkwijk DB, van Ommen B, Freidig AP, van der Greef J, de Graaf AA.

J Clin Bioinforma. 2011 Oct 26;1(1):29. doi: 10.1186/2043-9113-1-29.

12.

Simulating the physiology of athletes during endurance sports events: modelling human energy conversion and metabolism.

van Beek JH, Supandi F, Gavai AK, de Graaf AA, Binsl TW, Hettling H.

Philos Trans A Math Phys Eng Sci. 2011 Nov 13;369(1954):4295-315. doi: 10.1098/rsta.2011.0166.

13.

Measuring non-steady-state metabolic fluxes in starch-converting faecal microbiota in vitro.

Binsl TW, De Graaf AA, Venema K, Heringa J, Maathuis A, De Waard P, Van Beek JH.

Benef Microbes. 2010 Nov;1(4):391-405. doi: 10.3920/BM2010.0038.

PMID:
21831778
14.

Measuring non-steady-state metabolic fluxes in starch-converting faecal microbiota in vitro.

Binsl TW, De Graaf AA, Venema K, Heringa J, Maathuis A, De Waard P, Van Beek JH.

Benef Microbes. 2010 Nov;1(4):S1-7. No abstract available.

PMID:
21831768
15.

A physiologically-based kinetic model for the prediction of plasma cholesterol concentrations in the mouse.

van de Pas NC, Woutersen RA, van Ommen B, Rietjens IM, de Graaf AA.

Biochim Biophys Acta. 2011 May;1811(5):333-42. doi: 10.1016/j.bbalip.2011.02.002. Epub 2011 Feb 12.

PMID:
21320632
16.

Systematic construction of a conceptual minimal model of plasma cholesterol levels based on knockout mouse phenotypes.

van de Pas NC, Soffers AE, Freidig AP, van Ommen B, Woutersen RA, Rietjens IM, de Graaf AA.

Biochim Biophys Acta. 2010 Jun;1801(6):646-54. doi: 10.1016/j.bbalip.2010.02.009. Epub 2010 Feb 20.

PMID:
20176131
17.

Developing computational model-based diagnostics to analyse clinical chemistry data.

van Schalkwijk DB, van Bochove K, van Ommen B, Freidig AP, van Someren EP, van der Greef J, de Graaf AA.

Brief Bioinform. 2010 Jul;11(4):403-16. doi: 10.1093/bib/bbp071. Epub 2010 Jan 7.

PMID:
20056728
18.

Nutritional systems biology modeling: from molecular mechanisms to physiology.

de Graaf AA, Freidig AP, De Roos B, Jamshidi N, Heinemann M, Rullmann JA, Hall KD, Adiels M, van Ommen B.

PLoS Comput Biol. 2009 Nov;5(11):e1000554. doi: 10.1371/journal.pcbi.1000554. Epub 2009 Nov 26. Review.

19.

Profiling human gut bacterial metabolism and its kinetics using [U-13C]glucose and NMR.

de Graaf AA, Maathuis A, de Waard P, Deutz NE, Dijkema C, de Vos WM, Venema K.

NMR Biomed. 2010 Jan;23(1):2-12. doi: 10.1002/nbm.1418.

PMID:
19593762
20.

Improved cholesterol phenotype analysis by a model relating lipoprotein life cycle processes to particle size.

van Schalkwijk DB, de Graaf AA, van Ommen B, van Bochove K, Rensen PC, Havekes LM, van de Pas NC, Hoefsloot HC, van der Greef J, Freidig AP.

J Lipid Res. 2009 Dec;50(12):2398-411. doi: 10.1194/jlr.M800354-JLR200. Epub 2009 Jun 10.

21.

Linking phylogenetic identities of bacteria to starch fermentation in an in vitro model of the large intestine by RNA-based stable isotope probing.

Kovatcheva-Datchary P, Egert M, Maathuis A, Rajilić-Stojanović M, de Graaf AA, Smidt H, de Vos WM, Venema K.

Environ Microbiol. 2009 Apr;11(4):914-26. doi: 10.1111/j.1462-2920.2008.01815.x. Epub 2008 Dec 8.

PMID:
19128319
22.

Response of the central metabolism of Corynebacterium glutamicum to different flux burdens.

Marx A, Striegel K, de Graaf AA, Sahm H, Eggeling L.

Biotechnol Bioeng. 1997 Oct 20;56(2):168-80. doi: 10.1002/(SICI)1097-0290(19971020)56:2<168::AID-BIT6>3.0.CO;2-N.

PMID:
18636622
23.

Gaining insight into microbial physiology in the large intestine: a special role for stable isotopes.

de Graaf AA, Venema K.

Adv Microb Physiol. 2008;53:73-168. Review.

PMID:
17707144
24.

Application of liquid chromatography-mass spectrometry to measure the concentrations and study the synthesis of short chain fatty acids following stable isotope infusions.

Meesters RJ, van Eijk HM, ten Have GA, de Graaf AA, Venema K, van Rossum BE, Deutz NE.

J Chromatogr B Analyt Technol Biomed Life Sci. 2007 Jul 1;854(1-2):57-62. Epub 2007 Apr 8.

PMID:
17452031
25.

Identification of glucose-fermenting bacteria present in an in vitro model of the human intestine by RNA-stable isotope probing.

Egert M, de Graaf AA, Maathuis A, de Waard P, Plugge CM, Smidt H, Deutz NE, Dijkema C, de Vos WM, Venema K.

FEMS Microbiol Ecol. 2007 Apr;60(1):126-35. Epub 2007 Feb 22.

26.

Beyond diversity: functional microbiomics of the human colon.

Egert M, de Graaf AA, Smidt H, de Vos WM, Venema K.

Trends Microbiol. 2006 Feb;14(2):86-91. Epub 2006 Jan 10. Review.

PMID:
16406528
27.

Serial flux mapping of Corynebacterium glutamicum during fed-batch L-lysine production using the sensor reactor approach.

Drysch A, El Massaoudi M, Wiechert W, de Graaf AA, Takors R.

Biotechnol Bioeng. 2004 Mar 5;85(5):497-505.

PMID:
14760690
28.

Significance of phosphoglucose isomerase for the shift between heterolactic and mannitol fermentation of fructose by Oenococcus oeni.

Richter H, De Graaf AA, Hamann I, Unden G.

Arch Microbiol. 2003 Dec;180(6):465-70. Epub 2003 Nov 8.

PMID:
14608457
29.

Metabolic phenotype of phosphoglucose isomerase mutants of Corynebacterium glutamicum.

Marx A, Hans S, Möckel B, Bathe B, de Graaf AA, McCormack AC, Stapleton C, Burke K, O'Donohue M, Dunican LK.

J Biotechnol. 2003 Sep 4;104(1-3):185-97. Erratum in: J Biotechnol. 2003 Dec 5;106(1):113.

PMID:
12948638
32.
33.

Metabolic engineering for L-lysine production by Corynebacterium glutamicum.

de Graaf AA, Eggeling L, Sahm H.

Adv Biochem Eng Biotechnol. 2001;73:9-29. Review.

PMID:
11816814
34.
35.

A universal framework for 13C metabolic flux analysis.

Wiechert W, Möllney M, Petersen S, de Graaf AA.

Metab Eng. 2001 Jul;3(3):265-83.

PMID:
11461148
36.

Pathway analysis and metabolic engineering in Corynebacterium glutamicum.

Sahm H, Eggeling L, de Graaf AA.

Biol Chem. 2000 Sep-Oct;381(9-10):899-910. Review.

PMID:
11076021
37.

In vivo quantification of parallel and bidirectional fluxes in the anaplerosis of Corynebacterium glutamicum.

Petersen S, de Graaf AA, Eggeling L, Möllney M, Wiechert W, Sahm H.

J Biol Chem. 2000 Nov 17;275(46):35932-41.

38.

Response of the central metabolism in Corynebacterium glutamicum to the use of an NADH-dependent glutamate dehydrogenase.

Marx A, Eikmanns BJ, Sahm H, de Graaf AA, Eggeling L.

Metab Eng. 1999 Jan;1(1):35-48.

PMID:
10935753
41.

Determination of full 13C isotopomer distributions for metabolic flux analysis using heteronuclear spin echo difference NMR spectroscopy.

de Graaf AA, Mahle M, Möllney M, Wiechert W, Stahmann P, Sahm H.

J Biotechnol. 2000 Jan 28;77(1):25-35.

PMID:
10674212
42.

Bidirectional reaction steps in metabolic networks: IV. Optimal design of isotopomer labeling experiments.

Möllney M, Wiechert W, Kownatzki D, de Graaf AA.

Biotechnol Bioeng. 1999;66(2):86-103.

PMID:
10567067
43.

Bidirectional reaction steps in metabolic networks: III. Explicit solution and analysis of isotopomer labeling systems.

Wiechert W, Möllney M, Isermann N, Wurzel M, de Graaf AA.

Biotechnol Bioeng. 1999;66(2):69-85.

PMID:
10567066
44.

Metabolic state of Zymomonas mobilis in glucose-, fructose-, and xylose-fed continuous cultures as analysed by 13C- and 31P-NMR spectroscopy.

De Graaf AA, Striegel K, Wittig RM, Laufer B, Schmitz G, Wiechert W, Sprenger GA, Sahm H.

Arch Microbiol. 1999 May-Jun;171(6):371-85.

PMID:
10369893
45.

13C tracer experiments and metabolite balancing for metabolic flux analysis: comparing two approaches

Schmidt K, Marx A, de Graaf AA, Wiechert W, Sahm H, Nielsen J, Villadsen J.

Biotechnol Bioeng. 1998 Apr 5;58(2-3):254-7.

PMID:
10191397
46.
47.

Identification of a thiamin-dependent synthase in Escherichia coli required for the formation of the 1-deoxy-D-xylulose 5-phosphate precursor to isoprenoids, thiamin, and pyridoxol.

Sprenger GA, Schörken U, Wiegert T, Grolle S, de Graaf AA, Taylor SV, Begley TP, Bringer-Meyer S, Sahm H.

Proc Natl Acad Sci U S A. 1997 Nov 25;94(24):12857-62.

48.

Propionate oxidation in Escherichia coli: evidence for operation of a methylcitrate cycle in bacteria.

Textor S, Wendisch VF, De Graaf AA, Müller U, Linder MI, Linder D, Buckel W.

Arch Microbiol. 1997 Nov;168(5):428-36.

PMID:
9325432
49.

Bidirectional reaction steps in metabolic networks: II. Flux estimation and statistical analysis.

Wiechert W, Siefke C, de Graaf AA, Marx A.

Biotechnol Bioeng. 1997 Jul 5;55(1):118-35.

PMID:
18636450
50.

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