AIMC Topic: Single Molecule Imaging
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Learning-based event locating for single-molecule force spectroscopy.
Biochemical and biophysical research communications
Apr 8, 2021
Acquiring events massively from single-molecule force spectroscopy (SMFS) experiments, which is crucial for revealing important biophysical information, is usually not straightforward. A significant amount of human labor is usually required to identi...
CASSPER is a semantic segmentation-based particle picking algorithm for single-particle cryo-electron microscopy.
Communications biology
Feb 15, 2021
Particle identification and selection, which is a prerequisite for high-resolution structure determination of biological macromolecules via single-particle cryo-electron microscopy poses a major bottleneck for automating the steps of structure determ...
Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning.
Nature communications
Nov 17, 2020
Traces from single-molecule fluorescence microscopy (SMFM) experiments exhibit photophysical artifacts that typically necessitate human expert screening, which is time-consuming and introduces potential for user-dependent expectation bias. Here, we u...
DeepFRET, a software for rapid and automated single-molecule FRET data classification using deep learning.
eLife
Nov 3, 2020
Single-molecule Förster Resonance energy transfer (smFRET) is an adaptable method for studying the structure and dynamics of biomolecules. The development of high throughput methodologies and the growth of commercial instrumentation have outpaced the...
Software
Algorithms
Reproducibility of Results
Deep Learning
Markov Chains
Fluorescence Resonance Energy Transfer
Kinetics
False Positive Reactions
Molecular Dynamics Simulation
Nanotechnology
Single Molecule Imaging
User-Computer Interface
Normal Distribution
Fluorescent Dyes
Signal Processing, Computer-Assisted
Learning molecular dynamics with simple language model built upon long short-term memory neural network.
Nature communications
Oct 9, 2020
Recurrent neural networks have led to breakthroughs in natural language processing and speech recognition. Here we show that recurrent networks, specifically long short-term memory networks can also capture the temporal evolution of chemical/biophysi...
Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap.
Scientific reports
Jul 9, 2020
The analysis of neurotransmitters in the brain helps to understand brain functions and diagnose Parkinson's disease. Pharmacological inhibition experiments, electrophysiological measurement of action potentials, and mass analysers have been applied f...
DeepSTORM3D: dense 3D localization microscopy and PSF design by deep learning.
Nature methods
Jun 15, 2020
An outstanding challenge in single-molecule localization microscopy is the accurate and precise localization of individual point emitters in three dimensions in densely labeled samples. One established approach for three-dimensional single-molecule l...
Top-down machine learning approach for high-throughput single-molecule analysis.
eLife
Apr 8, 2020
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...
Machine learning for cluster analysis of localization microscopy data.
Nature communications
Mar 20, 2020
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...
Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data.
Communications biology
Jan 7, 2020
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...
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