Rovshan Sadygov

Rovshan Sadygov is an Associate Professor in the Department of Biochemistry & Molecular Biology at the University of Texas Medical Branch (UTMB). His research focuses on developing bioinformatics and statistical approaches to analyze high-throughput proteomics data, particularly using heavy water metabolic labeling and mass spectrometry. Key areas include protein turnover dynamics, signal transduction networks in epithelial-mesenchymal transition (EMT), and algorithmic advancements for proteomic data processing. Collaborations with experimentalists enable applications in NAFLD, heart failure, and respiratory disease models.

His work integrates stochastic modeling (e.g., Gaussian processes), machine learning (e.g., charge-state prediction), and software development (e.g., d2ome, ChromAlign) to address challenges in proteome analysis. Recent contributions include methods for optimizing experimental design in metabolic labeling studies, enhancing false discovery rate estimation, and refining protein turnover calculations using minimal timepoints.

Key projects involve:

• Quantifying proteome dynamics via deuterium incorporation in NAFLD and heart failure models.
• Uncovering signaling rewiring during EMT through phosphoproteomic mixed-effects modeling.
• Algorithmic innovations for peptide mass axis mapping and LC-MS data alignment.

His lab develops open-source tools like d2ome for automated protein turnover analysis and ChromAlign for chromatographic alignment, advancing quantitative proteomics workflows.