Research Mentors |
Institution and Department |
Research Focus |
Pitt – Computational Biology |
My research aims at understanding the molecular mechanisms of change and innovation by examining systems biology in the light of evolution and evolution in the light of systems biology. |
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Pitt – Chemistry, Physics, and the Center for Molecular and Materials Simulations |
Computational approaches to study ion channel gating and transport. |
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Pitt – Microbiology and Molecular Genetics |
Studying the evolution, ecology, and genome dynamics of experimental and clinical microbial populations. |
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Pitt – Bioengineering |
Multidisciplinary (mathematics, developmental biology, biophysics, and bioengineering) approach to understanding how molecular and genetic programs drive the formative tissue mechanics and self-assembly processes that generate living structures in developing embryos. |
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Pitt – Mathematics and the CMU-Center for the Neural Basis of Cognition |
Application of nonlinear dynamics to problems from cell biology and physiology. |
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Pitt – Computational & Systems Biology |
Mathematical (rule-based) modeling of intracellular signal transduction pathways. |
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Pitt – Computational Biology |
Quantitative imaging, microfluidics, and mathematical models to study how dynamic molecular signals transmit information in single cells. |
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Pitt – Cell Biology and Physiology |
Computational systems biology of signaling pathways. |
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Pitt – Computational Biology |
Development of mathematical models to study the dynamics of signaling networks; development of formal verification and machine learning based techniques for computational modeling and analysis of biological systems. |
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Pitt – Bioengineering |
Automation of learning big mechanisms in biology. Systems and synthetic biology. Emerging technologies and Internet of Things in medicine | |
Pitt – Chemical and Petroleum Engineering |
Systems medicine – mathematical modeling of disease (cancer, critical care/inflammation/sepsis, diabetes, cystic fibrosis) to support patient-tailored treatment decision-making. | |
CMU – Computer Science, Machine Learning, and The Language Technology Institute |
Using growing databases of viral sequences to build descriptive and generative models of viral molecular evolution. Modeling the evolution of Influenza. |
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Pitt – Mathematics |
Application of dynamical systems to modeling of inflammation and other aspects of physiology. |
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Pitt – Physics & Astronomy |
Understanding the factors that shape phenotypic variability in populations of bacteria and how the populations benefit from such variability. | |
Pitt – Chemical and Petroleum Engineering |
The Shoemaker Lab focuses on systems immunology. We model our body’s natural, dynamic responses to disease and develop mathematical tools to support these modeling challenges. Our model systems are multiscale with applications in pathogen detection and clearance, cancer immune evasion, and more. We are very interdisciplinary – most projects involve collaborations with UPMC or our international collaborators in Japan and Switzerland. | |
Pitt – Ophthalmology and Bioengineering |
Computational approaches to modeling neuronal communication and interactions, combined with experimental techniques to measure the activity of populations of neurons. |
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Pitt – Pharmacology and Chemical Biology |
The formation and repair of DNA damage in nuclear and mitochondrial genomes, with particular interest in the structure and function of proteins that mediate nucleotide excision repair and the role of oxidative stress in human disease. |
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Pitt – Computational Biology |
Computational and experimental quantitative biology approaches to study the dynamics and (genetic and epigenetic) regulatory mechanism of cell phenotype changes. |
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Pitt – Health Information Management |
Agent-based, equation-based, and statistical modeling of cardiovascular disease; comparative genomics and its applications in personalized medicine. |