Our research program focuses on developing integrative omics and data science approaches to elucidate the mechanisms underlying cardiac phenotypes. This involves employing analytical and computational methods to interrogate how protein dynamics orchestrate higher physiological functions in normal and diseased hearts. We also seek to unify these findings with the wealth of clinical and experimental findings only available through intensive mining of unstructured text data. Since our launch in 1996, this research program has authored over 200 manuscripts in cardiovascular medicine, biomedical informatics, and omics phenotyping. We utilize cutting-edge proteomics and biochemistry methods to understand the regulatory relationships between protein expression level and temporal dynamics, organelle functions, and cardiac phenotypes. We have optimized proteomics technologies to expand protein parameters observed on a large scale, including quantification of proteome-wide post-translational modifications (e.g., oxidative stress-sensitive post-translational modifications), localizations, and temporal dynamics to detect previously undiscovered disease signatures. We have also developed rich data resources and machine learning-powered computational tools for learning from massive volumes of clinical text, particularly clinical case reports.
Dr. Peipei Ping, the director of our research program, is strongly committed to supporting and mentoring the future generation of data-based biomedical researchers. She summarizes our mission as follows: “To provide an environment for students, fellows, and colleagues for creative work, and to remind everyone to share and enjoy the roses in life.”
Director: Peipei Ping, PhD (UCLA)
Co-Director: Karol E. Watson, MD, PhD (UCLA)
Chair of Curriculum Committee: Alex Bui, PhD (UCLA)