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Single Molecule Imaging

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Single-particle diffusional fingerprinting: A machine-learning framework for quantitative analysis of heterogeneous diffusion.

Proceedings of the National Academy of Sciences of the United States of America
Single-particle tracking (SPT) is a key tool for quantitative analysis of dynamic biological processes and has provided unprecedented insights into a wide range of systems such as receptor localization, enzyme propulsion, bacteria motility, and drug ...

Robust deep learning optical autofocus system applied to automated multiwell plate single molecule localization microscopy.

Journal of microscopy
We presenta robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image data acquisition times that may be impacted by defocusing resulting from drift of components, for ex...

Deep learning enables fast and dense single-molecule localization with high accuracy.

Nature methods
Single-molecule localization microscopy (SMLM) has had remarkable success in imaging cellular structures with nanometer resolution, but standard analysis algorithms require sparse emitters, which limits imaging speed and labeling density. Here, we ov...

Receptor tyrosine kinase MET ligand-interaction classified via machine learning from single-particle tracking data.

Molecular biology of the cell
Internalin B-mediated activation of the membrane-bound receptor tyrosine kinase MET is accompanied by a change in receptor mobility. Conversely, it should be possible to infer from receptor mobility whether a cell has been treated with internalin B. ...

Precise measurement of nanoscopic septin ring structures with deep learning-assisted quantitative superresolution microscopy.

Molecular biology of the cell
The combination of image analysis and superresolution microscopy methods allows for unprecedented insight into the organization of macromolecular assemblies in cells. Advances in deep learning (DL)-based object recognition enable the automated proces...

Development of Deep-Learning-Based Single-Molecule Localization Image Analysis.

International journal of molecular sciences
Recent developments in super-resolution fluorescence microscopic techniques (SRM) have allowed for nanoscale imaging that greatly facilitates our understanding of nanostructures. However, the performance of single-molecule localization microscopy (SM...

Field-dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging.

Nature methods
Single-molecule localization microscopy in a typical wide-field setup has been widely used for investigating subcellular structures with super resolution; however, field-dependent aberrations restrict the field of view (FOV) to only tens of micromete...

Machine-learning-powered extraction of molecular diffusivity from single-molecule images for super-resolution mapping.

Communications biology
While critical to biological processes, molecular diffusion is difficult to quantify, and spatial mapping of local diffusivity is even more challenging. Here we report a machine-learning-enabled approach, pixels-to-diffusivity (Pix2D), to directly ex...

Single-frame deep-learning super-resolution microscopy for intracellular dynamics imaging.

Nature communications
Single-molecule localization microscopy (SMLM) can be used to resolve subcellular structures and achieve a tenfold improvement in spatial resolution compared to that obtained by conventional fluorescence microscopy. However, the separation of single-...

An Unsupervised Classification Algorithm for Heterogeneous Cryo-EM Projection Images Based on Autoencoders.

International journal of molecular sciences
Heterogeneous three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is an important but very challenging technique for recovering the conformational heterogeneity of flexible biological macromolecules such as pro...