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Single Molecule Imaging

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Caveolae and scaffold detection from single molecule localization microscopy data using deep learning.

PloS one
Caveolae are plasma membrane invaginations whose formation requires caveolin-1 (Cav1), the adaptor protein polymerase I, and the transcript release factor (PTRF or CAVIN1). Caveolae have an important role in cell functioning, signaling, and disease. ...

Automated Stoichiometry Analysis of Single-Molecule Fluorescence Imaging Traces via Deep Learning.

Journal of the American Chemical Society
The stoichiometry of protein complexes is precisely regulated in cells and is fundamental to protein function. Singe-molecule fluorescence imaging based photobleaching event counting is a new approach for protein stoichiometry determination under phy...

Single-Particle Diffusion Characterization by Deep Learning.

Biophysical journal
Diffusion plays a crucial role in many biological processes including signaling, cellular organization, transport mechanisms, and more. Direct observation of molecular movement by single-particle-tracking experiments has contributed to a growing body...

Automated System for Small-Population Single-Particle Processing Enabled by Exclusive Liquid Repellency.

SLAS technology
Exclusive liquid repellency (ELR) describes an extreme wettability phenomenon in which a liquid phase droplet is completely repelled from a solid phase when exposed to a secondary immiscible liquid phase. Earlier, we developed a multi-liquid-phase op...

Accurate and rapid background estimation in single-molecule localization microscopy using the deep neural network BGnet.

Proceedings of the National Academy of Sciences of the United States of America
Background fluorescence, especially when it exhibits undesired spatial features, is a primary factor for reduced image quality in optical microscopy. Structured background is particularly detrimental when analyzing single-molecule images for 3-dimens...

Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data.

Communications biology
Single-molecule research techniques such as patch-clamp electrophysiology deliver unique biological insight by capturing the movement of individual proteins in real time, unobscured by whole-cell ensemble averaging. The critical first step in analysi...

Deep-learning with synthetic data enables automated picking of cryo-EM particle images of biological macromolecules.

Bioinformatics (Oxford, England)
MOTIVATION: Single-particle cryo-electron microscopy (cryo-EM) has become a powerful technique for determining 3D structures of biological macromolecules at near-atomic resolution. However, this approach requires picking huge numbers of macromolecula...

Machine learning for cluster analysis of localization microscopy data.

Nature communications
Quantifying the extent to which points are clustered in single-molecule localization microscopy data is vital to understanding the spatial relationships between molecules in the underlying sample. Many existing computational approaches are limited in...

Top-down machine learning approach for high-throughput single-molecule analysis.

eLife
Single-molecule approaches provide enormous insight into the dynamics of biomolecules, but adequately sampling distributions of states and events often requires extensive sampling. Although emerging experimental techniques can generate such large dat...

Large-scale single-molecule imaging aided by artificial intelligence.

Microscopy (Oxford, England)
Single-molecule imaging analysis has been applied to study the dynamics and kinetics of molecular behaviors and interactions in living cells. In spite of its high potential as a technique to investigate the molecular mechanisms of cellular phenomena,...