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Computational Biology

Modeling the dynamics of life systems: a multidimensional research journey

Computational models are essential tools that can be used to simultaneously explain and guide biological intuition. With increasingly high-resolution, high-throughput, and dynamic experimental data, computational biologists are better equipped to develop informed models that aim to characterize complex cellular responses and direct experimental design.

Membrane composition dictates fall of primary cilia and rise of cell cycle

A primary cilium is presented as a meso-scale device that senses and translates extracellular information into intracellular biochemical reactions. These input cues manifest in a variety of forms ranging from chemical to mechanical ones. Deregulation of these information transfer leads to human diseases known as ciliopathies. Due to its diffraction-limited dimension and semi-membrane-bound topology, a primary cilium has been a daunting compartment to visualize and manipulate signaling events on site.

High numerical aperture cryogenic localization microscopy: a technique for increased precision of super-resolution reconstructions

The precision of localization-based super-resolution microscopy techniques fundamentally relies on the point-spread function of the optical system and the number of photons one can collect. Here, we report that by using a high-numerical aperture objective lens and a custom cryogenic stage, we are able to increase photon yield by 2-3 fold over room temperature, thereby achieving more precise super-resolution reconstructions of complex subcellular structures.


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