Saccenti E - Search Results

1

Metabolomics of Milk Reflects a Negative Energy Balance in Cows.

Xu W, van Knegsel A, Saccenti E, van Hoeij R, Kemp B, Vervoort J. Xu W, et al. Among authors: saccenti e. J Proteome Res. 2020 Aug 7;19(8):2942-2949. doi: 10.1021/acs.jproteome.9b00706. Epub 2020 Jul 17. J Proteome Res. 2020. PMID: 32633519 Free PMC article. Review.

2

Probabilistic networks of blood metabolites in healthy subjects as indicators of latent cardiovascular risk.

Saccenti E, Suarez-Diez M, Luchinat C, Santucci C, Tenori L. Saccenti E, et al. J Proteome Res. 2015 Feb 6;14(2):1101-11. doi: 10.1021/pr501075r. Epub 2014 Dec 8. J Proteome Res. 2015. PMID: 25428344

3

Effects of Sample Size and Dimensionality on the Performance of Four Algorithms for Inference of Association Networks in Metabonomics.

Suarez-Diez M, Saccenti E. Suarez-Diez M, et al. Among authors: saccenti e. J Proteome Res. 2015 Dec 4;14(12):5119-30. doi: 10.1021/acs.jproteome.5b00344. Epub 2015 Oct 30. J Proteome Res. 2015. PMID: 26496246

4

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. Stroeve JH, et al. Among authors: saccenti e. Obesity (Silver Spring). 2016 Feb;24(2):379-88. doi: 10.1002/oby.21361. Obesity (Silver Spring). 2016. PMID: 26813527 Free article. Clinical Trial.

5

Approaches to Sample Size Determination for Multivariate Data: Applications to PCA and PLS-DA of Omics Data.

Saccenti E, Timmerman ME. Saccenti E, et al. J Proteome Res. 2016 Aug 5;15(8):2379-93. doi: 10.1021/acs.jproteome.5b01029. Epub 2016 Jul 7. J Proteome Res. 2016. PMID: 27322847

6

Entropy-Based Network Representation of the Individual Metabolic Phenotype.

Saccenti E, Menichetti G, Ghini V, Remondini D, Tenori L, Luchinat C. Saccenti E, et al. J Proteome Res. 2016 Sep 2;15(9):3298-307. doi: 10.1021/acs.jproteome.6b00454. Epub 2016 Aug 1. J Proteome Res. 2016. PMID: 27436276

7

Correlation Patterns in Experimental Data Are Affected by Normalization Procedures: Consequences for Data Analysis and Network Inference.

Saccenti E. Saccenti E. J Proteome Res. 2017 Feb 3;16(2):619-634. doi: 10.1021/acs.jproteome.6b00704. Epub 2016 Dec 15. J Proteome Res. 2017. PMID: 27977202

8

Plasma and Serum Metabolite Association Networks: Comparability within and between Studies Using NMR and MS Profiling.

Suarez-Diez M, Adam J, Adamski J, Chasapi SA, Luchinat C, Peters A, Prehn C, Santucci C, Spyridonidis A, Spyroulias GA, Tenori L, Wang-Sattler R, Saccenti E. Suarez-Diez M, et al. Among authors: saccenti e. J Proteome Res. 2017 Jul 7;16(7):2547-2559. doi: 10.1021/acs.jproteome.7b00106. Epub 2017 May 26. J Proteome Res. 2017. PMID: 28517934 Free PMC article.

9

Age and Sex Effects on Plasma Metabolite Association Networks in Healthy Subjects.

Vignoli A, Tenori L, Luchinat C, Saccenti E. Vignoli A, et al. Among authors: saccenti e. J Proteome Res. 2018 Jan 5;17(1):97-107. doi: 10.1021/acs.jproteome.7b00404. Epub 2017 Nov 21. J Proteome Res. 2018. PMID: 29090929

10

Milk Metabolomics Data Reveal the Energy Balance of Individual Dairy Cows in Early Lactation.

Xu W, Vervoort J, Saccenti E, van Hoeij R, Kemp B, van Knegsel A. Xu W, et al. Among authors: saccenti e. Sci Rep. 2018 Oct 25;8(1):15828. doi: 10.1038/s41598-018-34190-4. Sci Rep. 2018. PMID: 30361492 Free PMC article.

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