Clinical Systems Biology Team

Director and Principal Investigator, Clinical Systems Biology – Research Associate Professor, Dept. of Biomedical Engineering, Rochester Institute of TechnologyAdjunct Professor, Thomas H. Gosnell School of Life Sciences (GSoLS), Rochester Institute of TechnologyAdjunct Professor, Dept. of Psychology and Neuroscience, Nova Southeastern UniversityAdjunct Associate Professor, Dept. of Medicine, University of AlbertaAn engineer by training, Gordon Broderick, Ph.D., holds a doctorate in chemical engineering from the University of Montreal as well as a master's in chemical engineering and an undergraduate in mechanical engineering, both from McGill University.He completed post-doctoral training at McGill’s School of Computer Science in cancer genomics and a research fellowship in computational biochemistry at the University of Alberta, where he led a high-performance computing effort in modeling the molecular dynamics of intracellular life. Building on this study of complex emergent behavior in biology, Dr. Broderick’s current research efforts focus primarily on the emerging field of computational immunology and on how an integrated systems perspective might improve our understanding of immune dysfunction and autoimmunity in complex multi-system illness.This work is funded under a number of grants from the U.S. Department of Defense (CDMRP), the National Institutes of Health (NIH) and the U.S. Department of Veterans Affairs.A member of the editorial board for the new journal Systems Biomedicine (Taylor & Francis), Dr. Broderick also contributes as an associate editor to the journal BMC Systems Biology.Dr. Broderick recently moved his research from the University of Alberta and Nova Southeastern University to join the research community at RGH in developing new initiatives in the area of translational and computational medicine. The new Center will bring together a truly cross-disciplinary mix of investigators from the computational, clinical and basic life sciences with the goal of developing immune and hormone-based therapies for complex illnesses that are both safe and effective.

Associate Director, Clinical Systems Biology (Visiting Scientist) – Dr. Efroni is a distinguished Visiting Scientist; he is an Associate Professor at The Mina & Everard Goodman Faculty of Life Sciences, Bar Ilan University, Israel.He received his PhD from the Weizmann Institute and completed his post-doctoral work at the National Cancer Institute at the National Institutes of Health in Maryland. He returned to Israel to Bar Ilan University, where he now heads the Systems BioMedicine LabDr. Efroni has contributed significantly to the field of systems biomedicine, having designed and implemented an approach now known as Reactive Animation that facilitates the visual, computer legible and intuitive simulation of complex multi-agent systems through reactive technology of reactive animation. RA allows the experimenter to intervene mid-simulation, suggest new hypotheses for cellular and molecular interactions, apply them to the simulation and observe their resulting outcomes online. He has pioneered the use of these techniques to the modeling of cellular pathway logic, in particular in understanding various cancers. He has published extensively in Cell and Nature, and maintains ongoing research partnerships with colleagues at Harvard, MIT and the NIH.MORE

Cole Lyman., Chief Programmer, Team Leader, Computation – Cole Lyman is a graduate of Brigham Young University (BYU) with a B.Sc. in Computer Science where he specialized in bioinformatics and computational biology. He is currently completing his M.Sc. in Computer Science, also at BYU, where under the direction of Dr. Mark Clement he extended network theoretical aspects of Colored de Bruijn Graphs, developing novel applications to whole genome alignment, phylogenetic tree reconstruction, and genome wide association maps. Experienced in analyzing vast amounts of genomic data, he is well-versed in the design of distributed algorithms and will oversee the CCSB’s high-performance computing with alliance partner RIT, as well as new computing resources at the University of Buffalo’s Center for Computational Research (CCR). Leveraging his knowledge of these platforms he will focus on the development of robust and highly efficient code supporting the identification and simulation of complex biological regulatory networks such that code design is optimally suited for these large-scale computing resources. 

Team Leader, Bio-modeling – Dr. Morris is a research scientist with expertise in immunology, molecular biology, and computer science. At Virginia Tech, he studied intracellular signaling dynamics governing the innate immune response to bacterial endotoxin. At RGH, he has focused on mucosal immunology in children, including adaptive responses in the tonsils and adenoids and neutrophil responses in the nasopharynx. In the Clinical Systems Biology group, he applies an interdisciplinary skill set that spans applied computation, cellular and molecular biology to construct executable network models of living systems. He is currently active in developing comprehensive network models of signal transduction pathways as they apply to neurotoxic exposure, in collaboration with colleagues at the CDC NIOSH, as well as overseeing new initiatives in modeling cell-cell signaling mechanisms at various levels of biology ranging from molecular to organ systems as they apply to cancer biology, vaccine immunology and endocrine-immune disorders.

Team Leader, Behavioral Systems (Visiting Scientist) – Jonathan Tory Toole is originally from Georgia where he completed bachelors’ degrees in psychology and religion at the University of Georgia. He also holds Master’s degree in General Psychology from New York University (NYU), where he studied fear memory reconsolidation and pain processing. He is currently completing his Ph.D. in Clinical Psychology at Nova Southeastern University’s (NSU) College of Psychology and continues his work with the Broderick group in computational psychoneuroimmunology (PNI). Over the past 3 years he has brought his extensive background in clinical psychology to the team and become a key contributor to the integration of symptom severity constructs into multilevel models that bridge the molecular and cellular realms with symptom burden. He has used these models to study the characteristic network biology and bio-behavioral dynamics of complex chronic illnesses such as Gulf War illness (GWI) and Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), bringing a new perspective to understanding the molecular underpinnings of symptomatology and developing more effective treatment approaches.

Spencer Richman (B.S. / M.S. Bioinformatics, Senior, RIT). Spencer is completing a dual B.S. and M.S. degree in Bioinformatics at the Rochester Institute of Technology. His work focuses on the integration of pharmacological databases with drug target information derived from computational models of biological signaling at the intracellular and cellular levels as they apply to various complex chronic immune and endocrine disorders. Bringing to bear information about drug availability, contraindications and off-target effects through advanced applications of natural language processing, Spencer is developing novel criteria and methods to assess the accessibility of predicted treatment targets to drug repurposing strategies and their actionability in a clinical setting.

(B.S. /M.S. Bioinformatics, Senior, RIT). Gina is completing a dual B.S. and M.S. degree in Bioinformatics at the Rochester Institute of Technology. Her work focuses on the recovery from experimental data of logical rules that describe the multi-factorial behavioral mechanisms driving the decision to adhere to estrogen therapy (ET) in breast cancer patients.  In close collaboration with senior researchers at the MD Anderson Cancer Center in Houston, she will be exploring the use of various forms of probabilistic regression in describing the incremental evolution of behavioral constructs across a 5-year treatment period and how they change in their contribution to adherence. She will apply this to determine which patient groups might be at increased risk of discontinuation, as well as when and how best to intervene.

(B.S. / M.S. Bioinformatics, Fifth Year, RIT) Aditya is pursuing the dual Bachelors/ Masters degree at Rochester Institute of Technology. He is studying the recovery of cause-and-effect relationships linking molecular and cellular markers in large-scale biological networks from poorly sampled longitudinal data which cannot support classical rate equation modeling (e.g. pre and post treatment conditions). He will validate these novel interactions by testing their compatibility with known mechanisms extracted from the literature using natural language processing (NLP). This work is conducted as part of a larger ongoing collaborative effort with Duke University’s Institute for molecular physiology directed at understanding the basic mechanisms through which exercise promotes improved cardiometabolic health and how these effects might be reproduced pharmacologically in patients with compromised mobility.