Understanding protein function on a genome-wide scale is one of the central goals of biology 1. A fundamental task associated with this goal is the elucidation of cellular functional and interaction ...

Biomedical scientists are increasingly using deconvolution methods, those used to computationally analyze the composition of complex mixtures of cells. One of their challenges is to select one method ...

Deconvolution is a computational technique of increasing the resolution and SNR (signal to noise ratio) of images captured on an imaging system. Its use existed before the extensive use of confocal ...

Blasco, Andrea, Ted Natoli, Michael G. Endres, Rinat A. Sergeev, Steven Randazzo, Jin Hyun Paik, N.J. Maximilian Macaluso, Rajiv Narayan, Xiaodong Lu, David Peck ...

In last month’s column, we looked at the theory of deconvolution. This month, we’ll explore a hands-on application. Our goal will be to deconvolve a slightly blurred image and make it look sharp. Be ...

Zhongyao Ma, PhD, holds a bachelor’s degree in biology from Shanghai Jiao Tong University and a PhD in genetics and developmental biology from the University of Georgia, U.S. His research focused on ...

The retrospective identification of the drug targets that underlie an observed phenotypic response is termed target deconvolution. Target deconvolution can be achieved by numerous methods including; ...

a. MRA helps resolve the dense actin filaments with SIM imaging. b. MRA helps resolve the mitochondrial cristae cluster with LiveSR imaging. c. SecMRA helps better section the ER tubule structure. d.