Results 131 to 140 of about 3,760 (232)

VGAE-CCI: variational graph autoencoder-based construction of 3D spatial cell-cell communication network. [PDF]

Brief Bioinform
Zhang T, Zhang X, Wu Z, Ren J, Zhao Z, Zhang H, Wang G, Wang T.   +7 more
europepmc   +1 more source

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Investigating enzyme function by geometric matching of catalytic motifs

Protein Science, Volume 35, Issue 9, September 2026.
Abstract The rapidly growing universe of predicted protein structures offers opportunities for data driven exploration but requires computationally scalable and interpretable tools. We developed a method to detect catalytic features in protein structures, providing insights into enzyme function and mechanism.
Raymund E. Hackett, Ioannis G. Riziotis, Martin Larralde, António J. M. Ribeiro, Georg Zeller, Janet M. Thornton   +5 more
wiley   +1 more source

scMOG: A graph neural network method for regulatory relationship‐preserving single‐cell multi‐omics integration

Quantitative Biology, Volume 14, Issue 3, September 2026.
Abstract Single‐cell multi‐omics sequencing technology provides a powerful tool for studying cellular heterogeneity. However, beyond the challenges of sparsity, heterogeneity, and dimensionality differences, a critical challenge in multi‐omics data integration lies in preserving the true regulatory relationships among molecular features.
Yucheng Lu, Xun Zhang, Hongwei Li
wiley   +1 more source

Single‐cell marker gene clustering: A unified deep learning framework for marker gene‐based clustering of single‐cell RNA‐sequencing data

Quantitative Biology, Volume 14, Issue 3, September 2026.
Abstract Single‐cell RNA sequencing (scRNA‐seq) has transformed the study of cellular heterogeneity by making it possible to classify individual cells and their functional states. However, the analysis remains difficult because high dropout rates lead to sparse and noisy expression data.
Shahriar Rahman Niloy, Toushif Muktashid Hasan, Md. Saiduzzaman Apu, Fahim Hafiz, Salekul Islam, Riasat Azim   +5 more
wiley   +1 more source

VAE-Assisted Data Augmentation for Improved Molecular Prediction with Graph Neural Networks (GNNs) in Low-Data Regimes

Chemical Engineering Transactions
This study presents a novel approach to enhancing molecular property prediction through variational autoencoder (VAE)-assisted data augmentation in low-data regimes.
Gabriela C. Theis Marchan, Pegah Naghshnejad, Andrew Okafor, Jose A. Romagnoli   +3 more
doaj  

Multi‐Modal AI Approach in Depression Detection and Treatment: A Systematic Review of Last Decade

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Overview of multimodal approaches for depression detection and treatment. ABSTRACT Depression is a common and devastating mental health illness with serious personal and societal consequences. Despite advancing treatment techniques, there are still hurdles in the effective diagnosis and treatment of depression, such as prompt diagnosis, personalized ...
Smith K. Khare, Esmaeil S. Nadimi, U. Rajendra Acharya, Victoria Blanes‐Vidal   +3 more
wiley   +1 more source

MLN2SVG: domain-aware spatially variable gene detection using contrastive variational autoencoder and multi-level neighbor search. [PDF]

Brief Bioinform
Hussain S, Ayoub M, Ye F, Liu X.
europepmc   +1 more source

Consumer Behavior Analysis in Digital Marketing Using AI and Big Data Analytics: A Narrative Review and Methodological Taxonomy

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
AI and Big Data in Consumer Behavior Analysis. ABSTRACT The rapid expansion of digital consumer data has challenged traditional approaches to understanding behavior in digital marketing. Existing reviews often focus on individual methods and give limited guidance on how analytical techniques compare or how they should be selected for specific marketing
Leonidas Theodorakopoulos, Alexandra Theodoropoulou   +1 more
wiley   +1 more source

Spatiotemporal deep learning for real-time video-based deepfake detection using 3DCNN, 3DResNet, TCN, and VAE. [PDF]

Sci Rep
Agrawal P, Pathak D, Madaan V, Verma PK, Choo WO.   +4 more
europepmc   +1 more source