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Rafał Krzysztoń. I am interested in single-cell responses to internal and external signals and in emerging mechanisms governing collective cell behavior. In my endeavors, I use methods of synthetic and quantitative biology (i.e. controlled microenvironments, synthetic gene networks, microfluidics, nanomaterials and quantitative microscopy), complementing standard biological assays. Together with Prof. Dr. Balázsi, we develop gene regulation systems allowing to explore and control cancer metastasis and to counteract viral infection. By monitoring the single-cell expression of disease-related genes and correlating it with phenotype profiles (e.g. cell motility) we aim to gain quantitative insights into emergence and dynamics of those complex pathologies. (Balázsi lab) |
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Sridip Parui. The broad area of my research is the prediction of structures of biomolecules and the underlying pathways such as protein folding and conformational transitions. Knowing the three-dimensional structure and the related pathways is important for understanding biomolecular function. I believe MELD, which efficiently integrates external information with physics-based modeling, can serve these purposes. (Dill lab) |
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Rostam Razban applies tools from statistical mechanics to elucidate underlying forces in biological phenomena, such as “Why do proteins evolve differently?”, “What causes cells to age?” and “How do brain networks transition?” Emphasis is placed on developing biophysical models for which mathematical equations with experimentally measured parameters can be derived. (Dill lab | Bahar lab) |
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Lakshmanji Verma. I am interested in molecular-level motions of chemical, physical, and biophysical systems in solvents which manifest interesting microscopic phenomena such as phase separation, aggregation, and nucleation that eventually dictate macroscopic behaviors. My current work focuses on the development of a statistical mechanical water model which will significantly reduce the time and computational cost required to simulate complex phenomena (e.g. protein-ligand complexation dynamics). (Dill lab) |
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Ying-Jen Yang. Thermodynamic/energetic principles can be formulated for stochastic dynamical models of complex systems. These principles include fluctuation-dissipation relations, the landscape theory in stochastic thermodynamics, and the statistical thermodynamics of entropic forces. They are formulated purely from time symmetries and the limit theorems of stochastic models in the ideal data infinitus limit and are thus universal. I am generally interested in developing these theories and applying them to solve problems in cellular biology, neuroscience, and evolution biology. (Dill lab) |
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Anthony Bogetti. I am interested in developing methods for more efficient molecular dynamics simulations that enable more ambitious applications. During my PhD at the University of Pittsburgh in the lab of Lillian Chong, I worked on the weighted ensemble method, which uses splitting and merging to achieve more efficient sampling. I was a core developer of the WESTPA software package for weighted ensemble simulations. As a postdoc jointly in the labs of Ken Dill and Ivet Bahar, I am now interested in how the MELD sampling strategy, possibly combined with ENM methods, can further enhance molecular dynamics simulations and enable even more ambitious applications. (Dill lab | Bahar lab) |
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Anupam Banerjee. I work on the integration of Elastic Network Models (ENMs) into various biological systems, aiming to provide a more comprehensive understanding of the intricate relationship between the structural characteristics and functional properties of biomolecules. My research interests primarily revolve around the advancement of protein engineering frameworks, designed to measure and assess the consequences of diverse modifications on a protein's structural dynamics and functional attributes. Through an interdisciplinary approach, I contribute to shedding light on critical biological mechanisms, aiding in the development of novel therapeutic strategies and a deeper understanding of complex disease processes. (Bahar lab) |
