Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins.

Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images.

cellXpress: a fast and user-friendly software platform for profiling cellular phenotypes.

Background: High-throughput, image-based screens of cellular responses to genetic or chemical perturbations generate huge numbers of cell images. Automated analysis is required to quantify and compare the effects of these perturbations. However, few of the current freely-available bioimage analysis software tools are optimized for efficient handling of these images.

A Bayesian reconstruction method with marginalized uncertainty model for camera motion in microrotation imaging.

Reconstruction of a 3-D structure from multiple projection images requires prior knowledge of projection directions or camera motion parameters that describe the relative positions and orientations of 3-D structure with respect to the camera. These parameters can be estimated using, for instance, the conventional correlation alignment and feature-based methods. However, the alignment methods are not perfect, where the inaccuracy of the estimated motion parameters causes artifacts in the reconstruction.

A Bayesian reconstruction method for micro-rotation imaging in light microscopy.

The authors present a three-dimensional (3D) reconstruction algorithm and reconstruction-based deblurring method for light microscopy using a micro-rotation device. In contrast to conventional 3D optical imaging where the focal plane is shifted along the optical axis, micro-rotation imaging employs dielectric fields to rotate the object inside a fixed optical set-up. To address this entirely new 3D-imaging modality, the authors present a reconstruction algorithm based on Bayesian inversion theory and use the total variation function as a structure prior.