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Items: 48

1.

Calculation of the Protein Turnover Rate Using the Number of Incorporated 2H Atoms and Proteomics Analysis of a Single Labeled Sample.

Ilchenko S, Haddad A, Sadana P, Recchia FA, Sadygov R, Kasumov T.

Anal Chem. 2019 Nov 5. doi: 10.1021/acs.analchem.9b02757. [Epub ahead of print]

PMID:
31638786
2.

Another look at matrix correlations.

Borzou A, Yousefi R, Sadygov RG.

Bioinformatics. 2019 Nov 1;35(22):4748-4753. doi: 10.1093/bioinformatics/btz281.

PMID:
31081021
3.

d2ome, Software for in Vivo Protein Turnover Analysis Using Heavy Water Labeling and LC-MS, Reveals Alterations of Hepatic Proteome Dynamics in a Mouse Model of NAFLD.

Sadygov RG, Avva J, Rahman M, Lee K, Ilchenko S, Kasumov T, Borzou A.

J Proteome Res. 2018 Nov 2;17(11):3740-3748. doi: 10.1021/acs.jproteome.8b00417. Epub 2018 Oct 19.

4.

Hepatic Mitochondrial Defects in a Nonalcoholic Fatty Liver Disease Mouse Model Are Associated with Increased Degradation of Oxidative Phosphorylation Subunits.

Lee K, Haddad A, Osme A, Kim C, Borzou A, Ilchenko S, Allende D, Dasarathy S, McCullough A, Sadygov RG, Kasumov T.

Mol Cell Proteomics. 2018 Dec;17(12):2371-2386. doi: 10.1074/mcp.RA118.000961. Epub 2018 Aug 31.

PMID:
30171159
5.

Poisson Model To Generate Isotope Distribution for Biomolecules.

Sadygov RG.

J Proteome Res. 2018 Jan 5;17(1):751-758. doi: 10.1021/acs.jproteome.7b00807. Epub 2017 Dec 19.

6.

Increased serotransferrin and ceruloplasmin turnover in diet-controlled patients with type 2 diabetes.

Golizeh M, Lee K, Ilchenko S, Ösme A, Bena J, Sadygov RG, Kashyap SR, Kasumov T.

Free Radic Biol Med. 2017 Dec;113:461-469. doi: 10.1016/j.freeradbiomed.2017.10.373. Epub 2017 Oct 25.

7.

Predicting the protein half-life in tissue from its cellular properties.

Rahman M, Sadygov RG.

PLoS One. 2017 Jul 18;12(7):e0180428. doi: 10.1371/journal.pone.0180428. eCollection 2017.

8.

PPARgamma agonists rescue increased phosphorylation of FGF14 at S226 in the Tg2576 mouse model of Alzheimer's disease.

Hsu WJ, Wildburger NC, Haidacher SJ, Nenov MN, Folorunso O, Singh AK, Chesson BC, Franklin WF, Cortez I, Sadygov RG, Dineley KT, Rudra JS, Taglialatela G, Lichti CF, Denner L, Laezza F.

Exp Neurol. 2017 Sep;295:1-17. doi: 10.1016/j.expneurol.2017.05.005. Epub 2017 May 15.

9.

Integrative proteomic analysis reveals reprograming tumor necrosis factor signaling in epithelial mesenchymal transition.

Zhao Y, Tian B, Sadygov RG, Zhang Y, Brasier AR.

J Proteomics. 2016 Oct 4;148:126-38. doi: 10.1016/j.jprot.2016.07.014. Epub 2016 Jul 25.

10.

Proteome Dynamics Reveals Pro-Inflammatory Remodeling of Plasma Proteome in a Mouse Model of NAFLD.

Li L, Bebek G, Previs SF, Smith JD, Sadygov RG, McCullough AJ, Willard B, Kasumov T.

J Proteome Res. 2016 Sep 2;15(9):3388-404. doi: 10.1021/acs.jproteome.6b00601. Epub 2016 Aug 5.

11.

Gaussian Process Modeling of Protein Turnover.

Rahman M, Previs SF, Kasumov T, Sadygov RG.

J Proteome Res. 2016 Jul 1;15(7):2115-22. doi: 10.1021/acs.jproteome.5b00990. Epub 2016 Jun 9.

12.

Using SEQUEST with theoretically complete sequence databases.

Sadygov RG.

J Am Soc Mass Spectrom. 2015 Nov;26(11):1858-64. doi: 10.1007/s13361-015-1228-5. Epub 2015 Aug 4.

13.

Tracer-based estimates of protein flux in cases of incomplete product renewal: evidence and implications of heterogeneity in collagen turnover.

Zhou H, Wang SP, Herath K, Kasumov T, Sadygov RG, Previs SF, Kelley DE.

Am J Physiol Endocrinol Metab. 2015 Jul 15;309(2):E115-21. doi: 10.1152/ajpendo.00435.2014. Epub 2015 May 26.

14.

Mixed-effects model of epithelial-mesenchymal transition reveals rewiring of signaling networks.

Desai P, Yang J, Tian B, Sun H, Kalita M, Ju H, Paulucci-Holthauzen A, Zhao Y, Brasier AR, Sadygov RG.

Cell Signal. 2015 Jul;27(7):1413-25. doi: 10.1016/j.cellsig.2015.03.024. Epub 2015 Apr 8.

15.

Current Bioinformatics Challenges in Proteome Dynamics using Heavy Water-based Metabolic Labeling.

Kasumov T, Willard B, Sadygov RG.

J Data Mining Genomics Proteomics. 2014 Feb;5(1):e112. No abstract available.

16.

Cardiac mitochondrial proteome dynamics with heavy water reveals stable rate of mitochondrial protein synthesis in heart failure despite decline in mitochondrial oxidative capacity.

Shekar KC, Li L, Dabkowski ER, Xu W, Ribeiro RF Jr, Hecker PA, Recchia FA, Sadygov RG, Willard B, Kasumov T, Stanley WC.

J Mol Cell Cardiol. 2014 Oct;75:88-97. doi: 10.1016/j.yjmcc.2014.06.014. Epub 2014 Jul 1.

17.

Use of singular value decomposition analysis to differentiate phosphorylated precursors in strong cation exchange fractions.

Sadygov RG.

Electrophoresis. 2014 Dec;35(24):3498-503. doi: 10.1002/elps.201400053. Epub 2014 Jul 24.

18.

Cognitive enhancing treatment with a PPARγ agonist normalizes dentate granule cell presynaptic function in Tg2576 APP mice.

Nenov MN, Laezza F, Haidacher SJ, Zhao Y, Sadygov RG, Starkey JM, Spratt H, Luxon BA, Dineley KT, Denner L.

J Neurosci. 2014 Jan 15;34(3):1028-36. doi: 10.1523/JNEUROSCI.3413-13.2014.

19.

The cancer drug tamoxifen: a potential therapeutic treatment for spinal cord injury.

Guptarak J, Wiktorowicz JE, Sadygov RG, Zivadinovic D, Paulucci-Holthauzen AA, Vergara L, Nesic O.

J Neurotrauma. 2014 Feb 1;31(3):268-83. doi: 10.1089/neu.2013.3108. Epub 2013 Dec 11.

20.

Use of theoretical peptide distributions in phosphoproteome analysis.

Kalita M, Kasumov T, Brasier AR, Sadygov RG.

J Proteome Res. 2013 Jul 5;12(7):3207-14. doi: 10.1021/pr4003382. Epub 2013 Jun 19.

21.

Assessment of cardiac proteome dynamics with heavy water: slower protein synthesis rates in interfibrillar than subsarcolemmal mitochondria.

Kasumov T, Dabkowski ER, Shekar KC, Li L, Ribeiro RF Jr, Walsh K, Previs SF, Sadygov RG, Willard B, Stanley WC.

Am J Physiol Heart Circ Physiol. 2013 May;304(9):H1201-14. doi: 10.1152/ajpheart.00933.2012. Epub 2013 Mar 1.

22.

Cognitive enhancement with rosiglitazone links the hippocampal PPARγ and ERK MAPK signaling pathways.

Denner LA, Rodriguez-Rivera J, Haidacher SJ, Jahrling JB, Carmical JR, Hernandez CM, Zhao Y, Sadygov RG, Starkey JM, Spratt H, Luxon BA, Wood TG, Dineley KT.

J Neurosci. 2012 Nov 21;32(47):16725-35a. doi: 10.1523/JNEUROSCI.2153-12.2012.

23.

High mass accuracy phosphopeptide identification using tandem mass spectra.

Sadygov RG.

Int J Proteomics. 2012;2012:104681. doi: 10.1155/2012/104681. Epub 2012 Jul 15.

24.

Generalized Linear and Mixed Models for Label-Free Shotgun Proteomics.

Leitch MC, Mitra I, Sadygov RG.

Stat Interface. 2012;5(1):89-98.

25.

Detection of structural and metabolic changes in traumatically injured hippocampus by quantitative differential proteomics.

Wu P, Zhao Y, Haidacher SJ, Wang E, Parsley MO, Gao J, Sadygov RG, Starkey JM, Luxon BA, Spratt H, Dewitt DS, Prough DS, Denner L.

J Neurotrauma. 2013 May 1;30(9):775-88. doi: 10.1089/neu.2012.2391. Epub 2012 Sep 20.

26.

Improved mass defect model for theoretical tryptic peptides.

Mitra I, Nefedov AV, Brasier AR, Sadygov RG.

Anal Chem. 2012 Mar 20;84(6):3026-32. doi: 10.1021/ac203255e. Epub 2012 Mar 7.

27.

Plasma proteome dynamics: analysis of lipoproteins and acute phase response proteins with 2H2O metabolic labeling.

Li L, Willard B, Rachdaoui N, Kirwan JP, Sadygov RG, Stanley WC, Previs S, McCullough AJ, Kasumov T.

Mol Cell Proteomics. 2012 Jul;11(7):M111.014209. doi: 10.1074/mcp.M111.014209. Epub 2012 Mar 5.

28.

A parallel method for enumerating amino acid compositions and masses of all theoretical peptides.

Nefedov AV, Sadygov RG.

BMC Bioinformatics. 2011 Nov 7;12:432. doi: 10.1186/1471-2105-12-432.

29.

Examining troughs in the mass distribution of all theoretically possible tryptic peptides.

Nefedov AV, Mitra I, Brasier AR, Sadygov RG.

J Proteome Res. 2011 Sep 2;10(9):4150-7. doi: 10.1021/pr2003177. Epub 2011 Aug 9.

30.

Comparison of Programmatic Approaches for Efficient Accessing to mzML Files.

Gilski MJ, Sadygov RG.

J Data Mining Genomics Proteomics. 2011 Jan 1;2(1). pii: 109.

31.

Bioinformatics Tools for Mass Spectrometry-Based High-Throughput Quantitative Proteomics Platforms.

Nefedov AV, Gilski MJ, Sadygov RG.

Curr Proteomics. 2011 Jul;8(2):125-137.

32.

Measuring protein synthesis using metabolic ²H labeling, high-resolution mass spectrometry, and an algorithm.

Kasumov T, Ilchenko S, Li L, Rachdaoui N, Sadygov RG, Willard B, McCullough AJ, Previs S.

Anal Biochem. 2011 May 1;412(1):47-55. doi: 10.1016/j.ab.2011.01.021. Epub 2011 Jan 20.

33.

SVM model for quality assessment of medium resolution mass spectra from 18O-water labeling experiments.

Nefedov AV, Gilski MJ, Sadygov RG.

J Proteome Res. 2011 Apr 1;10(4):2095-103. doi: 10.1021/pr1012174. Epub 2011 Feb 23.

34.

Using power spectrum analysis to evaluate (18)O-water labeling data acquired from low resolution mass spectrometers.

Sadygov RG, Zhao Y, Haidacher SJ, Starkey JM, Tilton RG, Denner L.

J Proteome Res. 2010 Aug 6;9(8):4306-12. doi: 10.1021/pr100642q.

35.

Altered retinoic acid metabolism in diabetic mouse kidney identified by O isotopic labeling and 2D mass spectrometry.

Starkey JM, Zhao Y, Sadygov RG, Haidacher SJ, Lejeune WS, Dey N, Luxon BA, Kane MA, Napoli JL, Denner L, Tilton RG.

PLoS One. 2010 Jun 14;5(6):e11095. doi: 10.1371/journal.pone.0011095.

36.

[Sinus lifting operation peculiarities after radical maxillary sinusotomy].

Sadygov RV, Orlov AA, Biziaev AF, Spitsina VI.

Stomatologiia (Mosk). 2009;88(3):69-71. Russian.

PMID:
19692954
37.

A new probabilistic database search algorithm for ETD spectra.

Sadygov RG, Good DM, Swaney DL, Coon JJ.

J Proteome Res. 2009 Jun;8(6):3198-205. doi: 10.1021/pr900153b.

38.
39.

ChromAlign: A two-step algorithmic procedure for time alignment of three-dimensional LC-MS chromatographic surfaces.

Sadygov RG, Maroto FM, Hühmer AF.

Anal Chem. 2006 Dec 15;78(24):8207-17.

PMID:
17165809
40.

Central limit theorem as an approximation for intensity-based scoring function.

Sadygov R, Wohlschlegel J, Park SK, Xu T, Yates JR 3rd.

Anal Chem. 2006 Jan 1;78(1):89-95.

PMID:
16383314
41.

Large-scale database searching using tandem mass spectra: looking up the answer in the back of the book.

Sadygov RG, Cociorva D, Yates JR 3rd.

Nat Methods. 2004 Dec;1(3):195-202. Review.

PMID:
15789030
42.

MS1, MS2, and SQT-three unified, compact, and easily parsed file formats for the storage of shotgun proteomic spectra and identifications.

McDonald WH, Tabb DL, Sadygov RG, MacCoss MJ, Venable J, Graumann J, Johnson JR, Cociorva D, Yates JR 3rd.

Rapid Commun Mass Spectrom. 2004;18(18):2162-8.

PMID:
15317041
43.

A model for random sampling and estimation of relative protein abundance in shotgun proteomics.

Liu H, Sadygov RG, Yates JR 3rd.

Anal Chem. 2004 Jul 15;76(14):4193-201.

PMID:
15253663
44.
45.

A correlation algorithm for the automated quantitative analysis of shotgun proteomics data.

MacCoss MJ, Wu CC, Liu H, Sadygov R, Yates JR 3rd.

Anal Chem. 2003 Dec 15;75(24):6912-21.

PMID:
14670053
47.

Code developments to improve the efficiency of automated MS/MS spectra interpretation.

Sadygov RG, Eng J, Durr E, Saraf A, McDonald H, MacCoss MJ, Yates JR 3rd.

J Proteome Res. 2002 May-Jun;1(3):211-5.

PMID:
12645897
48.

Shotgun identification of protein modifications from protein complexes and lens tissue.

MacCoss MJ, McDonald WH, Saraf A, Sadygov R, Clark JM, Tasto JJ, Gould KL, Wolters D, Washburn M, Weiss A, Clark JI, Yates JR 3rd.

Proc Natl Acad Sci U S A. 2002 Jun 11;99(12):7900-5.

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