Laufer Junior Fellows

dignon; Dzmitry Padhorny.


Postdoctoral Associates

dignon; Gregory Dignon. The goal of my research is to develop theory, and computation-based approaches to aid in designing drug formulations for monoclonal antibodies. I am particularly interested in modeling protein-cosolvent interactions, and exploring how they may disrupt protein self-interactions, thus reducing high concentration viscosity and aggregation propensity.
rafal 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.
sridip 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.
rostam 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.
bhanita Bhanita Sharma. My research focuses on probing the protein aggregation and fibril formation using MELD simulation method. Protein aggregation involves self-assembly of normally soluble proteins into insoluble amyloid fibrils, which are linked to several diseases. I believe that the powerful approach of combined physics-based atomistic model with enhanced conformational sampling techniques can provide important insights into the early stages of protein aggregation and fibril formation, structural characteristics of protein fibrils and binding mode of amyloid inhibitors.