Article

DeepGANnel: Synthesis of fully annotated single molecule patch-clamp data using generative adversarial networks

2020-06-27

Abstract excerpt

Development of automated analysis tools for “single ion channel” recording is hampered by the lack of available training data. For machine learning based tools, very large training sets are necessary with sample-by-sample point labelled data (e.g., 1 sample point every 100microsecond). In an experimental context, such data are labelled with human supervision, and whilst this is feasible for simple experimental ana...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 171938b7-c2f1-55fd-89b5-ab20de2a9b45
DOI: 10.1101/2020.06.25.171918

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

DeepGANnel: Synthesis of fully annotated single molecule patch-clamp data using generative adversarial networksDOI 10.1101/2020.06.25.171918Read

Large-scale synthetic data enable digital twins of human excitable cellsSemantic proximity Read

ElectroPhysiomeGAN: Generation of Biophysical Neuron Model Parameters from Recorded Electrophysiological ResponsesSemantic proximity Read

Association between AI-Based Electrocardiographic Age from Wearable Devices and Atrial Fibrillation: The PROPHECG-Age Single StudySemantic proximity Read

Data Imbalance in Cardiac Health Diagnostics Using CECG-GANSemantic proximity Read

Enhancing ECG Signal Data through Denoising Features with Transformer Generative Adversarial Networks for Model Classification 1D-CNNSemantic proximity Read

Model-Driven Analysis of ECG Using Reinforcement LearningSemantic proximity Read

Generating realistic neurophysiological time series with denoising diffusion probabilistic modelsSemantic proximity Read

Generative Adversarial Network Model to Classify Human Induced Pluripotent Stem Cell-Cardiomyocytes based on Maturation LevelSemantic proximity Read

A Generative AI Framework to Predict Cardiomyocyte Contraction Function from Single Static ImagesSemantic proximity Read

Quantum-Refined Latent Diffusion: A Hybrid Generative Framework for Imbalanced ECG ClassificationSemantic proximity Read

General-purpose time-series foundation models enable sample-efficient transfer learning in retinal electrophysiologySemantic proximity Read

Comparative Analysis of Data Augmentation for Clinical ECG Classification with STARSemantic proximity Read