Understanding the structure of biomolecules is crucial for a detailed analysis of their biological function. In some cases, substantial information is available using techniques such as X-ray crystallography and NMR. Computer simulation can then be directly applied to study the dynamic properties of these molecules or molecular complexes. In other cases, only genomic sequence data is available. Structure prediction then becomes an important task in its own right. COB faculty are developing and using a variety of algorithms (Enhanced Sampling, Fast Electrostatics, Energy Minimization, and Molecular Dynamics) for both prediction and improved dynamical modeling, including quantum effects. These techniques are being applied to the study of protein and DNA structure and function, transcription complexes, and polymerase mechanisms. Modeling and simulation is also being used to characterize molecular mechanisms important to biomedicine, such as DNA repair and blood coagulation pathways.
The study of gene products, interactions and networks, which is at the core of existing and emerging genomic sciences, offers unparalleled opportunities for a productive integration of computational and experimental approaches. The challenge of gathering, integrating and analyzing genomic information (large collections of sequences, structures, and functional annotations for protein, DNA, and RNA) demands innovative quantitative formulations, algorithms and conceptual frameworks, and can only be addressed by multidisciplinary research teams. Current research at NYU/MSSM covers structural, functional and comparative genomics, proteomics, transcriptomics, and ribonomics. Our faculty are involved both in the development of novel computational and experimental techniques, and in cutting-edge applications of these techniques in biology and biomedicine.
Understanding physiological processes -- cell growth and death, blood coagulation, brain function, heart function -- and diseases requires development of computational algorithms that model biological structures at scales ranging from individual molecules to multi-component aggregates to physiological organs and networks to organisms. The goal of developing and analyzing realistic models of physiological systems is to understand the basic mechanisms of function, as well the development of improved disease diagnosis and treatment (e.g., vaccines) and of new medical instruments (e.g., artificial hearts and valves). COB faculty work in the areas of signal transduction, neuronal network processing and brain function, cellular biophysics, and cardiac dynamics and function.
Cellular and Biological Imaging
The field of biomedical imaging encompasses both the microscopic analysis of fixed and living cells and the visualization of macroscopic physiological structures using computerized tomography (CT scanners), magnetic resonance imaging, ultrasound imaging and radioisotope scans. It has led to enormous advances in both basic biology and medicine. The field is highly interdisciplinary - involving sophisticated mathematical and physical modeling, signal processing, electromagnetic analysis, and the numerical solution of inverse problems. Major areas of research include 1) the development of automatic, quantitative, image segmentation and analysis tools in microscopy and 2) the improvement of reconstruction methods for magnetic resonance imaging.