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
Learning Continuous Decomposable Models Using Mutual Information and Statistical Copulas. [PDF]
Desuó Neto L +3 more
europepmc +1 more source
Plant Genetic Engineering: Technological Pathways, Application Scenarios, and Future Directions
This review maps the fast‐evolving landscape of plant genetic engineering, linking enabling platforms with trait‐focused applications in architecture optimization, stress resilience, yield improvement, and quality enhancement. It highlights how genome editing, transgenic strategies, and emerging multi‐gene approaches reshape breeding pipelines, while ...
Peilin Wang +4 more
wiley +1 more source
Interpretable Sensor Change Detection via Conditional Cauchy-Schwarz Divergence. [PDF]
Wang W, Shen Y, Ni Y, Wu W.
europepmc +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
Regression approaches for modeling genotype-environment interaction and making predictions into unseen environments. [PDF]
Hrachov M +3 more
europepmc +1 more source
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Robust Distributed High-Dimensional Regression: A Convoluted Rank Approach. [PDF]
Wu M.
europepmc +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
Explicit Compression Degradation Estimations for Low-Sampling Single-Pixel Imaging using Hadamard Basis. [PDF]
Zhang H, Cao J, Zhou C, Yao H, Hao Q.
europepmc +1 more source

