Regina R. Monaco, Ph.D. is a Neuroscience Research Fellow at the Ronin Institute where she studies properties of biological neural networks using machine learning and thermodynamic (entropic) measures to aid in deconvolution of raw data (EEG, fMRI, spike-trains) generated from mammalian connectomes to discover system-wide functional correlations. She also studies computational dynamic models of small neural networks and the emergent characteristic properties and patterns of these networks.
She has worked as a Senior Researcher, Fellow, or Adjunct Assistant Professor at a number of universities over her career, including University of Texas San Antonio, NYU, Syracuse University, University of Illinois Urbana, Columbia University, NASA Ames, and most recently, Mount Sinai Health System. Her research utilizes theoretical computational methods to define dynamic and mechanistic interactions of macromolecular complexes, including drug/DNA complexes, DNA repair complexes including THIIH, structure and activity of the XPD subunit, properties of porphyrins covalently tethered to DNA octamers, 3D structural predictions of small RNA prebiotic polymers, genetic replication fidelity, and luminescent biomolecules, such as GFP-related molecules. She also studies smaller biological molecules including bacteriorhodopsin (MD simulations), ras-p21, EFGR, G-binding proteins, phytoene synthase (PSY-1), GNRH, and rap-1a. She worked on a bioinformatic study of pharmaceutical agents to find off-label uses by determining which receptors these molecules bind to..