AIMC Topic: Single Molecule Imaging
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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
Dec 23, 2019
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...
Caveolae and scaffold detection from single molecule localization microscopy data using deep learning.
PloS one
Aug 26, 2019
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. ...
Single-Particle Diffusion Characterization by Deep Learning.
Biophysical journal
Jun 22, 2019
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
Jun 10, 2019
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...
Automated Stoichiometry Analysis of Single-Molecule Fluorescence Imaging Traces via Deep Learning.
Journal of the American Chemical Society
Apr 18, 2019
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...
Linking of single-molecule experiments with molecular dynamics simulations by machine learning.
eLife
May 3, 2018
Single-molecule experiments and molecular dynamics (MD) simulations are indispensable tools for investigating protein conformational dynamics. The former provide data, such as donor-acceptor distances, whereas the latter give atomistic information, ...
Effect of dacarbazine on CD44 in live melanoma cells as measured by atomic force microscopy-based nanoscopy.
International journal of nanomedicine
Dec 18, 2017
CD44 ligand-receptor interactions are known to be involved in regulating cell migration and tumor cell metastasis. High expression levels of CD44 correlate with a poor prognosis of melanoma patients. In order to understand not only the mechanistic ba...
Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning.
Cell systems
May 15, 2024
Image-based spatial transcriptomics methods enable transcriptome-scale gene expression measurements with spatial information but require complex, manually tuned analysis pipelines. We present Polaris, an analysis pipeline for image-based spatial tran...
Bound2Learn: a machine learning approach for classification of DNA-bound proteins from single-molecule tracking experiments.
Nucleic acids research
Aug 20, 2021
DNA-bound proteins are essential elements for the maintenance, regulation, and use of the genome. The time they spend bound to DNA provides useful information on their stability within protein complexes and insight into the understanding of biologica...
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
Aug 3, 2021
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 ...
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