Journal of Data Mining in Genomics & Proteomics

Rovshan Sadygov

Rovshan Sadygov
Department of Biochemistry and Molecular Biology
University of Texas, USA

Biography

Rovshan Sadygov is an Assistant Professor at Bioinformatics, Department of Biochemistry and Molecular Biology, University of Texas, USA.

Research Interest

Our research interests are in computational analysis of mass spectral data from proteomics experiments to infer biological information. For these purposes we adopt methods of probability/statistics, signal processing and pattern recognition to analyze mass spectral data and use biological knowledge base for interpretations. Proteomics research plays important role in the studies of primary structure of proteins, protein interaction networks, biomarker discovery, post-translational modifications and signaling pathways. Proteomics experiments generate large amounts of data relevant to the protein content and complexity of a sample. The interpretation of these data requires efficient bioinformatics tools to process, store, visualize and disseminate the data. We develop algorithms for error tolerant database search, protein grouping, spectral quality assessment, in silico sequence hybridization (to reduce sequence redundancy), spectral library search, elemental composition determination and for processing chromatographic surfaces for alignments in time and mass-to-charge ratio domains and normalization in abundance domain, peak detection, background subtraction and peak area integration. These algorithms will serve as a base for inferring primary protein content information of a biological sample. We will then use this information to generate probabilistic models for protein interaction networks, signaling pathways, statistical models for potential biomarker discovery and validation, for absolute and relative protein quantification.