Majority‐Voting Overlapping Method for Error Correction in DNA Data Storage
Advanced Intelligent Discovery, EarlyView.We propose an overlapping‐based majority‐voting method for DNA data storage error correction. By aligning multiple reads and choosing the most frequent base per position, it suppresses substitution errors without prior models. Validated on synthetic and real sequencing data, it achieves high‐fidelity, scalable, and cost‐effective reconstruction ...
Thi Bich Ngoc Nguyen +5 more
wiley +1 more source
Iterated Residual Graph Convolutional Neural Network for Personalized Three-Dimensional Reconstruction of Left Myocardium from Cardiac MR Images. [PDF]
Sensors (Basel), 2023 Wang X, Yuan Y, Liu M, Niu Y.
europepmc +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Leveraging molecular-QTL co-association to predict novel disease-associated genetic loci using a graph convolutional neural network. [PDF]
PLoS OneNg-Kee-Kwong J, Bretherick AD.
europepmc +2 more sources
Improved Graph Convolutional Neural Network for Dance Tracking and Pose Estimation. [PDF]
Comput Intell Neurosci, 2022 Zhang L.
europepmc +1 more source
Graph Convolutional Neural Network Approaches for Exploring and Discovering Brain Dynamics [PDF]
University of Technology Sydney. Faculty of Engineering and Information Technology.This thesis delves into Motor Imagery Electroencephalography (MI-EEG) classification, aiming to refine precision and deepen the understanding of the complex dynamics in ...
Almohammadi, Abdullah
core +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Nonintrusive Power Load Decomposition Based on Adaptive Graph Convolutional Neural Network. [PDF]
Sensors (Basel)Zhao P, Wei J, Wang L, Qiu Y.
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
EEG Cross-Subject Taste Classification Method: A Meta-Learning Wavelet Graph Convolutional Neural Network Under Sweet and Bitter Stimuli. [PDF]
Biosensors (Basel)Wang H, Men H, Shi Y.
europepmc +1 more source