Giulia Palermo is a computational biophysicist with expertise in molecular simulations. She is an Assistant Professor at the University of California Riverside, where she interfaces computational biophysics with structural biology, chemistry and biochemistry to clarify the mechanistic action of biological systems of key importance, emerging genome editing technologies and directed evolution strategies.
She is a native of Italy where she earned her PhD in 2013 from the Italian Institute of Technology, working in the group of Dr. Marco De Vivo. She has been an early post-doctoral scientist in the group of Prof. Ursula Rothlisberger at the Swiss Federal Institute of Technology (EPFL), where she earned expertise in ab-initio Molecular Dynamics and its application to biological systems. In 2016, she has been awarded a Swiss National Science Foundation (NSF) post-doctoral fellowship to join the group of Prof. J. Andrew McCammon at the University of California San Diego, where she specialised in novel multiscale methods enabling the study of increasingly realistic biological systems.
Dominic Biondo – graduate student
Dominic project focuses on unraveling the function of non-coding RNAs, which regulate gene expression via a variety of yet unknown mechanisms. Toward, this aim, he will apply a variety of computational methods, from classical and enhanced sampling methods, to QM/MM and cryo-EM refinement.
Marco Medrano – undergraduate student
Marco is an undergraduate student in the Department of Bioengineering at UCR. His current research interests in the Palermo lab are understanding the structure, function and mechanisms of new emerging classes of CRISPR systems, which are being harnessed for genome editing. In his project, he is applying bioinformatic tools and molecular dynamics.
Ponmathi Jayaseelan – undergraduate student
Ponmathi is an undergraduate student interested in learning molecular dynamics simulations of proteins and nucleic acids. Her project involves the application of MD simulations and of unconventional analysis methods, including dimensionality reduction methods, correlation analysis and Markov state models.