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Selected Publications

  1. Deberneh HM. , Abdelrahman DR, Verna SK, Linares JJ, Murton AJ, Russell WK, Kuyumcu-Martinez MN, Miller BF, Sadygov RG. Quantifying Label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling. Communications Chemistry, 2023, 6 (1):72.

  2. Deberneh HM. , Abdelrahman DR, Verna SK, Linares JJ, Murton AJ, Russell WK, Kuyumcu-Martinez MN, Miller BF, Sadygov RG. A large-scale LC-MS dataset of murine liver proteome from time course of heavy water metabolic labeling. Scientific Data| (2023) 10:635.

  3. Deberneh, HM, Sadygov RG, Retention Time Alignment for Protein Turnover Studies Using Heavy Water Metabolic Labeling J. Proteome Res 2023, 2023, 22, 2, 410–419.

  4. Sadygov RG, Protein turnover models for LC–MS data of heavy water metabolic labeling Briefings in Bioinformatics, 2022, 23(2), 1–14.

  5. Deberneh, HM, Sadygov RG, Software tool for Visualization and Validation of Protein Turnover Rates Using Heavy Water Metabolic Labeling and LC-MS Int. J. Mol. Sci. 2022, 23(23), 14620.

  6. Sadygov RG, Using Heavy Mass Isotopomers for Protein Turnover in Heavy Water Metabolic Labeling Journal of Proteome Research,2021; 20(4):2035-2041. doi: 10.1021/acs.jproteome.0c00873.

  7. Borzou A. and Sadygov RG, A Novel Estimator of the Interaction Matrix in Graphical Gaussian Model of Omics Data Using the Entropy of Non-Equilibrium Systems. Bioinformatics, 2021; 37(6):837-44.

  8. Sadygov RG, Avva J, Rahman M, Lee K, Sergei Ilchenko S, Kasumov T., and Borzou A.,, Correction to “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”. Journal of Proteome Research 2021 20 (10), 4912

  9. Borzou A. and Sadygov RG, AUsing the Entropy of Non-Equilibrium Systems of Molecules to Estimate the Interaction Matrix in Graphical Gaussian Models of Omics Data. Biophysics, 2021.

  10. Sadygov RG, Partial Isotope Profiles are Sufficient for Protein Turnover Analysis using Closed-form Equations of Mass Isotopomer Dynamics, Analytical Chemistry, 2020, v. 92, 21, 14747–14753.

  11. Sadygov RG , High Resolution Mass Spectrometry for in vivo Proteome Dynamics using Heavy Water Metabolic Labeling, International Journal of Molecular Sciences, 2020, v. 21, 7821.

  12. Sadygov V. , Zhang W. , and Sadygov RG, Timepoint Selection Strategy for in Vivo Proteome Dynamics from Heavy Water Metabolic Labeling and LC-MS Journal of Proteome Research; 2020, v. 19, 2105−2112.

  13. Borzou A. , Sadygov V. , Zhang W. , and Sadygov RG, Proteome dynamics from heavy water metabolic labeling and peptide tandem mass spectrometry, International Journal of Mass Spectrometry, 2019, 445, 116194.

  14. Borzou A. , Yousefi R., and Sadygov RG, Another Look at Matrix Correlations, Bioinformatics, 35(22), 2019, 4748–4753.

  15. Ilchenko S., Haddad A., Sadana P., Recchia F.B., Sadygov RG , Kasumov T., Calculation of the Protein Turnover Rate Using the Number of Incorporated 2H atoms and Proteomics Analysis of Single Labeled Sample, Analytical Chemistry, 2019, 91, 22, 14340-14351.

  16. Sadygov RG, Avva J, Rahman M, Lee K, Sergei Ilchenko S, Kasumov T., and Borzou A., 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, Journal of Proteome Research, 2018 17(11):3740-3748.

  17. Lee K, Haddad A, Osme A, Kim C, Borzou A, Ilchenko S, Allende D, Dasarathy S, McCullough A, Sadygov RG, and Kasumov T., Hepatic mitochondrial defects in a mouse model of NAFLD are associated with increased degradation of oxidative phosphorylation subunits, Molecular and Cellular Proteomics. 2018; 17(12):2371-2386.

  18. Sadygov RG, Poisson Model To Generate Isotope Distribution for Biomolecules. Journal of Proteome Research 2018, 17 (1), 751-758.

  19. Rahman M, Sadygov RG, Predicting the protein half-life in tissue from its cellular properties, PLoS ONE 2017 12(7):e0180428. doi: 10.1371/journal.pone.0180428.

  20. Golizeh M., Lee K., Ilchenko S., Osme A., Bena J., Sadygov RG, Kashyap S., and Kasumov T. Increased Serotransferring and Ceruloplasmin turnover in diet-controlled patients with Type 2 Diabetes. Free Radical Biology and Medicine, 2017;113:461-469.

  21. 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. PPARgamma agonists rescue increased phosphorylation of FGF14 at S226 in the Tg2576 mouse model of Alzheimer's disease. Experimental Neurology. 2017; 295:1-17.

  22. Rahman M, Previs SF, Kasumov T, Sadygov RG, Gaussian Process Modeling of Protein Turnover, Journal of Proteome Research, 2016:15(7):2115-22.

  23. Zhao Y, Tian B, Sadygov RG, Zhang Y, Brasier AR, Integrative proteomic analysis reveals reprograming tumor necrosis factor signaling in epithelial mesenchymal transition, Journal of Proteomics. 2016;148:126-138.

  24. Li L, Bebek G, Previs SF, Smith JD, Sadygov RG, McCullough AJ, Willard B, Kasumov T., Proteome Dynamics Reveals Pro-Inflammatory Remodeling of Plasma Proteome in a Mouse Model of NAFLD, Journal of Proteome Research, 2016;15(9):3388–3404.  

  25. Sadygov RG, Using SEQUEST with Theoretically Complete Sequence Databases, Journal of American Society of Mass Spectrometry. 2015;26(11):1858-64.

  26. Zhou H., Wang S.-P., Herath K., Kasumov T., Sadygov RG, Previs S., and Kelley D., Tracer-based estimates of protein flux in cases of incomplete product renewal: Implications of collagen heterogeneity, American Journal Physiology - Endocrinology and Metabolism, 2015;3092(2):E115-21.

  27. Desai P., Yang J., Tian B., Sun H., Kalita M., Ju H., Paulucci-Holthauzen A., Zhao Y., Brasier A.R., and Sadygov RG; Mixed-Effects Model of Epithelial-Mesenchymal Transition Reveals Rewiring of Signaling Networks. Cellular Signalling, 2015;27:1413–1425.

  28. Kasumov T., Willard B., Li L., Sadygov R. G., Previs S. Dynamic Proteomics with heavy water: Instrumentation, Data Analysis and Biological Application. Proteomics/Book 2”, 2015; DOI:10.5772/61776, InTech Publishing.

  29. Sadygov RG; Use of Singular Value Decomposition Analysis to Differentiate Phosphorylated Precursors in Strong Cation Exchange Fractions. Electrophoresis. 2014; 35(24):2498-503.

  30. Shekar KC, Li L, Dabkowski ER, Xu W, Ribeiro RF Jr, Hecker PA, Recchia FA, Sadygov RG, Willard B, Kasumov T, Stanley WC. Cardiac mitochondrial proteome dynamics with heavy water reveals stable rate of mitochondrial protein synthesis in heart failure despite decline in mitochondrial oxidative capacity. Journal of Molecular and Cellular Cardiology, 2014;75:88-97.

  31. Nenov MN, Laezza F, Haidacher SJ, Zhao Y, Sadygov RG, Starkey JM, Spratt H, Luxon BA, Dineley KT, Denner L., Cognitive Enhancing Treatment with a PPARγ Agonist Normalizes Dentate Granule Cell Presynaptic Function in Tg2576 APP Mice. Journal Neuroscience. 2014;34(3):1028-36.

  32. Willard B., Kasumov T., Sadygov RG, Current Bioinformatics Challenges in Proteome Dynamics using Heavy Water-based Metabolic Labeling, Data Mining in Genomics and Proteomics 2014:5:e112.

  33. Guptarak, J.; Wu, Y.; Wiktorowicz, E.J.; Sadygov RG ; Zivadinovic, D.; Palucci AA.; Nesic, O., Cancer drug Tamoxifen: A potential therapeutic treatment for spinal cord injury, Journal of Neurotrauma, 2014;31(3):268-83.

  34. Kalita M, Kasumov T, Brasier AR, Sadygov RG, Use of Theoretical Peptide Distributions in Phosphoproteome Analysis. Journal of Proteome Research, 2013;12(7):3207-14.

  35. Kasumov T, Dabkowski ER, Shekar KC, Li L, Ribeiro RF Jr, Walsh K, Previs SF, Sadygov RG, Willard B, Stanley WC., Assessment of cardiac proteome dynamics with heavy water: slower protein synthesis rates in interfibrillar than subsarcolemmal mitochondria. American Journal of Physiology - Heart and Circulatory Physiology, 2013;304(9):H1201-14.

  36. Mitra I., Nefedov AV, Brasier A. R., Sadygov RG, Improved mass defect model for theoretical tryptic peptides, Analytical Chemistry, 2012;84(6):3026-32.

  37. Li L., Willard B., Rachdaoui N., Kirwan JP., Sadygov RG, Stanley WC, Previs S., McCullough A. J., Kasumov T., Plasma proteome dynamics: analysis of lipoproteins and acute phase response proteins with 2H2O metabolic labeling. Molecular and Cellular Proteomics. 2012;11(7).

  38. 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., Cognitive enhancement with rosiglitazone links the hippocampal PPARγ and ERK MAPK signaling pathways. Journal of Neuroscience, 2012;32(47):16725-35.

  39. Sadygov RG, High Mass Accuracy Phosphopeptide Identification Using Tandem Mass Spectra. International Journal of Proteomics. 2012;2012:104681.

  40. Wu P., Zhao Y., Haidacher S.J., Wang E., Parsley M.O., Gao J., Sadygov RG, Starkey J.M., Luxon B.A., Spratt H., Dewitt D.S., Prough D.S., Denner L., Detection of Structural and Metabolic Changes in Traumatically Injured Hippocampus by Quantitative Differential Proteomics, Journal of Nuerotrauma, 2012:29:1–14

  41. Leitch MC, Mitra I., Sadygov RG, Generalized Linear and Mixed Models for Label-Free Shotgun Proteomics, Statistics and Its Interface, 2012;5(1):89-98

  42. Nefedov AV, Mitra I, Brasier AR, Sadygov RG , Examining Troughs in the Mass Distribution of All Theoretically Possible Tryptic Peptides, Journal of Proteome Research 2011;10:4150.

  43. Nefedov AV, Sadygov RG , A Parallel Method for Enumerating Amino Acid Compositions, BMC Bioinformatics, 2011:12:432.

  44. Nefedov AV, Gilski MJ, Sadygov RG, Bioinformatics Tools for Mass Spectrometry-Based High-Throughput Quantitative Proteomics Platforms, Current Proteomics, 2011;8:125-37.

  45. Nefedov A., Gilski M., Sadygov RG, An SVM Model for Quality Assessment of Medium Resolution Mass Spectra from 18O-water Labeling Experiments, Journal of Proteome Research, 2011;10(4):2095-103.

  46. Gilski M. J., Sadygov RG, Comparison of Programmatic Approaches for Efficient Accessing to mzML Files, Data Mining in Genomics and Proteomics 2011;2:109.

  47. Kasumov T, Ilchenko S, Li L, Rachdaoui N, Sadygov RG, Willard B, McCullough AJ, Previs S., Measuring protein synthesis using metabolic 2H labeling, high-resolution mass spectrometry, and an algorithm, Analytical Biochemistry. 2011;412(1):47-55.

  48. Sadygov RG, Zhao Y., Haidacher SJ, Starkey J. M., Tilton R. G. and Denner L., Using Power Spectrum Analysis to Evaluate 18O-Water Labeling Data Acquired from Low Resolution Mass Spectrometers, Journal of Proteome Research, 2010;9:4306–4312.

  49. Starkey JM, Zhao Y, Sadygov RG, Haidacher SJ, LeJeune WS, Dey N, Luxon BA, Kane MA, Napoli JL, Denner L, Tilton RG., Altered Retinoic Acid Metabolism in Diabetic Mouse Kidney Identified by 18O Isotopic Labeling and 2D Mass Spectrometry, PLoS ONE; 2010:5:1-10.

  50. Sadygov RG, Good DM, Swaney DL, Coon J, A New Probabilistic Database Search Algorithm for ETD Spectra, Journal of Proteome Research, 2009;8:3198-205.

  51. Sadygov RG, Hao Z, Huhmer A, Charger: a combination of signal processing and statistical learning algorithms for charge state determination from MS/MS. Analytical Chemistry, 2008:80:376-386.

  52. Park Z.-Y., Sadygov RG, Clark J, Yates JR, Assigning in vivo Carbamylation and Acetylation in Human Lens Proteins using Tandem Mass Spectrometry and Database Searching. International Journal of Mass Spectrometry, 2007;259:161-173.

  53. Sadygov RG, and V Zabrouskov, Database Search of High Mass Resolution Data, Journal of Biomolecular Techniques, 2007, 18(1), 6.

  54. Sadygov RG, Maroto FM, Huhmer A, ChromAlign: A Two-Step Algorithmic Procedure for Time Alignment of Three Dimensional LC-MS Chromatographic Surfaces. Analytical Chemistry, 2006;78:8207-8217.

  55. Sadygov RG, Wohlschlegel J., Park S.K., Xu T. and Yates J.R. III, Central Limit Theorem as an Approximation for Intensity-Based Scoring Function. Analytcial Chemistry, 2006;78:89-95.

  56. Sadygov RG, Cociorva D., Yates J.R. III., Large-scale Database Searching using Tandem Mass Spectra: Looking up the answer in the Back of the Book. Nature Methods, 2004;1:195-202.

  57. McDonald W.H., Tabb D.L., Sadygov RG, MacCoss M.J., Venable J., Grauman J., Johnson J.R., Cociorva D. and Yates J.R. III., MS1, MS2, and SQT – three unified, compact, and easily parsed file formats for the storage of shotgun proteomic spectra and identifications. Rapid Communications in Mass Spectrometry, 2004;18:2162-2168.

  58. Liu H, Sadygov RG, and Yates J.R. III, A Model for Random Sampling and Estimation of Relative Protein Abundance in Shotgun Proteomics. Analytical Chemistry, 2004;76:4193-4201.

  59. Sadygov RG, Liu H., and Yates J.R. III, Statistical Models for Protein Validation using Tandem Mass Spectral Data and Protein Amino Acid Sequence Databases, Analytical Chemistry, 2004;76:1664-1671.

  60. Sadygov RG , and Yates J. R. III, A Hypergeometric Probability Model for Protein Identification and Validation using Tandem Mass Spectral Data and Protein Sequence Databases. Analytical Chemistry 2003;75:3792-3798.

  61. MacCoss M. J., Wu C. C., Liu H., Sadygov RG, Yates J. R., III, A Correlation Algorithm for the Automated Quantitative Analysis of Shotgun Proteomics Data. Analytical Chemistry 2003;75:6912-6921.

  62. Sadygov RG, Eng J., Durr E., Saraf A., McDonald H.W., MacCoss J.M., and Yates J.R. III, Code Developments to Improve the Efficiency of Automated MS/MS Spectra Interpretation, Journal of Proteome Research, 2002:1:211.

  63. MacCoss M.J., McDonald W.H., Saraf A., Sadygov RG, Clark J.M., Tasto J.J., Gould K.L., Wolters D., Washburn M., Weiss A., Clark J.I., and Yates J.R. III, Shotgun identification of protein modifications from protein complexes and lens tissue, Proceedings of National Academy of Sciences USA, 2002;99:7900-7905.

  64. Sadygov RG, Neuhauser D., Dynamics of primary charge separation in bacterial photosynthesis using the multilevel Redfield-Davies secular approach, International Journal of Quantum Chemistry 2002;87:254-263.

  65. Anderson S.M., Sadygov RG, Neuhauser D., Non-adiabatic interactions in molecular dynamics, in Encyclopedia of Chemical Physics and Physical Chemistry , Edited by J. Moore, and N. Spencer, Institute of Physics, 2001:v2, ISBN 9780750303132, IP264., CRC Press.

  66. Sadygov RG, and Yarkony D.R., Unusual conical intersections in the Jahn-Teller effect: The electronically excited states of Li3. Journal of Chemical Physics, 1999;110:3639.

  67. Sadygov RG, and Yarkony D.R. On the Adiabatic to Diabatic States Transformation in the Presence of a Conical Intersection: A Most Diabatic Basis from the Solution to a Poisson's Equation. 1. Journal of Chemical Physics, 1998;109:20.

  68. Sadygov RG, and Yarkony D.R., Electronic structure aspects of the spin-forbidden reaction CH3(X 2A″2)+N(4S)→HCN(X 1Σ+)+H2(X 1Σ+g), Journal of Chemical Physics, 1997;107:4994.

  69. Sadygov RG, Rostas J., Taieb G. and Yarkony D.R., Resonances in the predissociation of the A 2ΠΩ state of MgBr, Journal of Chemical Physics, 1997;106(10):4091-101.

  70. Wang S.J., Cai J.J., Sadygov RG, and Lim E.C., Intramolecular charge-transfer and solvent-polarity dependence of radiative decay-rate in photoexcited dinaphthylamines, Journal of Physical Chemistry, 1995;99:7416.

  71. Sadygov RG, and Lim E.C., A Theoretical Study of the Structure and Energetics of Stacked Dimers of Polycyclic Aromatic Hydrocarbons: Application of INDO 1/S Method to Singlet Excimers of Naphthalene and Phenanthrene, Chemical Physics Letters, 1994;225:44.

  72. Chen D., Sadygov RG, and Lim E.C., Intramolecular Photoassociation and Photoinduced Charge Transfer in Bridged Diaryl Compounds: A Semiempirical MO Study of Intramolecular Charge Transfer in the Excited Singlet States of Dinaphthylamines, Journal of Physical Chemistry, 1994;98:2018.

  73. Parush O.V., Sadygov RG, and Kukushkin A.K., An influence of asymmetry of RC dimer polar surroundings on the electron transfer process, Biofizika 1994;39(5):848-854.

  74. Sadygov RG and Kukushkin A.K., The Effect of Broadening of Vibrational Levels on the Primary Charge Separation Processes in Bacterial Photosynthesis, Biofizika 1991:36(6):990.

  75. Kukushkin A.K., and Sadygov RG, Activationless Electron Transfer in the Primary Charge Separation of Bacterial Photosynthesis. Vestnik MGU, Ser. 3 Physics and Astronomy 1991;32:84.