Alexandre Cunha

Filtering Cryoimages of Cells and Macromolecular Complexes

Electron cryomicroscopy is a remarkable technology enabling new discoveries at sub-cellular scales making the cryoelectron microscope one of the most valuable and advanced assets in the toolbox of the contemporary structural biologist. Studies at such scale aim to understand the structure and function of the macromolecular machinery responsible for regulating cell mechanisms with the ultimate goal of simulating and fabricating living cells to perform specific tasks, such as inhibiting HIV infection and transform plants in fuel.

One major difficulty in cryoimaging is the overwhelming amount of noise which prevents a straightforward and clear identification of conformation of structures in cells and protein complexes. In this presentation I will describe some challenges in cryoimaging and present our recent work in denoising cryoimages using nonlocal unsupervised filtering. Our denoising algorithm is a rewriting of the nonlocal mean filter of Buades et. al. and as such it does not assume a particular model for the noise present in the corrupted image but rather reveals it during the computations. It builds on the separable property of neighborhood filtering to offer a fast parallel and vectorized implementation in contemporary shared memory computer architectures while reducing the theoretical computational complexity of the original filter.