Results 91 to 100 of about 40,778 (262)
SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao +11 more
wiley +1 more source
Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi +4 more
wiley +1 more source
ABSTRACT Extracellular vesicles (EVs) are nanoscale mediators of intercellular communication with diverse molecular cargoes that reflect their cell of origin. Advances in isolation, detection, and single‐particle analytics have revealed increasing molecular and functional heterogeneity, while exposing limitations in how EV identity and activity are ...
David J. Lundy +8 more
wiley +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions
Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized ...
Beatrice Foroni +2 more
openaire +3 more sources
A Modular and Programmable Cas13d Platform for RNA Single Nucleotide Variant Detection
A scenario‐guided Cas13d platform enables configurable single nucleotide variant ribonucleic acid diagnostics through rule‐based guide design and ribonucleic acid binding domain engineering, supporting amplification‐free ultrasensitive detection and amplification‐coupled robust detection for accurate mutation classification in clinical tumor specimens.
Zeyu Wang +8 more
wiley +1 more source
Modelling Co-movements and Tail Dependency in the International Stock Market via Copulae [PDF]
This paper examines international equity market co-movements using time-varying copulae. We examine distributions from the class of Symmetric Generalized Hyperbolic (SGH) distributions for modelling univariate marginals of equity index returns.
Eckhard Platen, Katja Ignatieva
core
Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu +5 more
wiley +1 more source
Noise-Adaptive SOGI–HOSM Observer for Sensorless Speed Control of Induction Machines
This study addresses the limitations of traditional sliding-mode observers in sensorless induction motor control under complex, non-Gaussian noise profiles.
Kobena Badu Enyam +4 more
doaj +1 more source
Stable Diffusion Models Reveal a Persisting Human–AI Gap in Visual Creativity
This study examines visual creativity in humans and generative AI using the TCIA framework. Human artists outperform AI overall, yet structured human guidance substantially improves AI outputs and evaluations. Findings reveal that alignment with human creativity depends critically on contextual framing, highlighting both the promise and current ...
Silvia Rondini +8 more
wiley +1 more source

