Rovshan G. Sadygov

Larry Denner2
Heidi Spratt2
Bruce A Luxon2
Jonathan M Starkey2
2Larry Denner
2Heidi Spratt
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The purpose of this work is to develop and verify statistical models for protein identification using peptide identifications derived from the results of tandem mass spectral database searches. Recently we have presented a probabilistic model for peptide identification that uses hypergeometric distribution to approximate fragment ion matches of database(More)
Tamoxifen (TMX) is a selective estrogen receptor modulator that can mimic the neuroprotective effects of estrogen but lacks its systemic adverse effects. We found that TMX (1 mg/day) significantly improved the motor recovery of partially paralyzed hind limbs of male adult rats with thoracic spinal cord injury (SCI), thus indicating a translational potential(More)
Hippocampal network hyperexcitability is considered an early indicator of Alzheimer's disease (AD) memory impairment. Some AD mouse models exhibit similar network phenotypes. In this study we focused on dentate gyrus (DG) granule cell spontaneous and evoked properties in 9-month-old Tg2576 mice that model AD amyloidosis and cognitive deficits. Using(More)
We previously reported that the peroxisome proliferator-activated receptor γ (PPARγ) agonist rosiglitazone (RSG) improved hippocampus-dependent cognition in the Alzheimer's disease (AD) mouse model, Tg2576. RSG had no effect on wild-type littermate cognitive performance. Since extracellular signal-regulated protein kinase mitogen-activated protein kinase(More)
BACKGROUND Numerous metabolic pathways have been implicated in diabetes-induced renal injury, yet few studies have utilized unbiased systems biology approaches for mapping the interconnectivity of diabetes-dysregulated proteins that are involved. We utilized a global, quantitative, differential proteomic approach to identify a novel retinoic acid hub in(More)
BACKGROUND Enumeration of all theoretically possible amino acid compositions is an important problem in several proteomics workflows, including peptide mass fingerprinting, mass defect labeling, mass defect filtering, and de novo peptide sequencing. Because of the high computational complexity of this task, reported methods for peptide enumeration were(More)
We describe a stochastic model to compute in vivo protein turnover rate constants from stable-isotope labeling and high-throughput liquid chromatography-mass spectrometry experiments. We show that the often-used one- and two-compartment nonstochastic models allow explicit solutions from the corresponding stochastic differential equations. The resulting(More)
Phosphoproteomics is a powerful analytical platform for identification and quantification of phosphorylated peptides and assignment of phosphorylation sites. Bioinformatics tools to identify phosphorylated peptides from their tandem mass spectra and protein sequence databases are important part of phosphoproteomics. In this work, we discuss general(More)
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