Jose Puglisi, PhD

Assistant Professor of Physiology, Biostatistics

Office: (916) 686-7682
Fax: (916) 686-7310
Jose.Puglisi@cnsu.edu

Jose Puglisi, PhD

Education

  • PhD. Electrical Engineering, Univesidade Estadual de Campinas, Brazil

About

Dr. Jose Luis Puglisi served as a Research Assistant Scientist at the University of California, Davis, Department of Pharmacology from 2008 – 2015, and, from 2005 – 2008, held a Research Assistant Professor position at Loyola University in Chicago, Stritch School of Medicine, following his pos-doctoral training.

Dr. Puglisi has received academic honors for scientific excellence from the Institute of Electrical and Electronic Engineering, the American Society for Pharmacology and Experimental Therapeutics, and the American Heart Association. He has published over 25 papers in peer reviewed journals (Circulation Research, Science Signaling) developed copyrighted software for use in research and teaching (including LabHEART and LabAXON that are freely available on the web at www.labheart.org), and is a member of the Biophysical Society, the Society for Mathematical Biology, and Cardiac Muscle Society.

Research Interest

Mathematical Modeling of the Biological Systems - Involves the development of computer programs that integrate the diverse mechanisms involved in the cell function into a mathematical framework. In particular, I focus my research in using in silico experiments to determine potential pharmacological targets. This approach complements the experimental work (in vitro and in vivo models) and helps to optimize the development of new compounds to treat disease.

Analysis and Processing of Confocal Microscopy Images - Involves the development of algorithms to analyze confocal microscopy images. The availability of high-speed, two dimensional confocal microscopes together with increasing number of fluorescent probes presents scientists with both opportunities and challenges to study spatial and temporal dynamics of neuronal processes. The challenge resides in detecting subtle changes in the fluorescence signal of the probe. New algorithms need to be developed that detect them automatically and distinguish noise from statistical significant fluorescence signals.