Web Link Our research focuses on the theoretical development of bioinformatics and statistical approaches to address challenges posed in biological inferences from high-throughput proteomics data, and their application to biological problems. For this purpose, we develop algorithms for peak detection and quantification, identification of structures in multivariate data, stochastic time-course modeling to extract dynamical features, construction of protein networks and error control in the resulting inferences. In collaboration with our experimentalist colleagues, we apply these techniques in various systems for systematic studies of post-translational modifications and, proteome dynamics, signal transductions and mass informatics. Our goal is to promote identification of functional dysregulations associated with changes in the state of a biological system.
Publications/Creative Works
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Affiliations
Research Consortia
The Gulf Coast Consortium for Bioinformatics
Training Grants
NLM Training Program in Biomedical Informatics & Data Science for Predoctoral and Postdoctoral Fellows
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