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
Estimation of Lockdowns' Impact on Well-Being in Selected Countries: An Application of Novel Bayesian Methods and Google Search Queries Data. [PDF]
Drachal K, González Cortés D.
europepmc +1 more source
This study uncovers a recipient‐derived monocyte‐to‐macrophage trajectory that drives inflammation during kidney transplant rejection. Using over 150 000 single‐cell profiles and more than 850 biopsies, the authors identify CXCL10+ macrophages as key predictors of graft loss.
Alexis Varin +16 more
wiley +1 more source
Spatio-temporal variations in neonatal mortality rates in Ghana: An application of hierarchical Bayesian methods. [PDF]
Kwami Takramah W, Dwomoh D, Aheto JMK.
europepmc +1 more source
A Scalable Framework for Comprehensive Typing of Polymorphic Immune Genes from Long‐Read Data
SpecImmune introduces a unified computational framework optimized for long‐read sequencing to resolve over 400 highly polymorphic immune genes. This scalable approach achieves high‐resolution typing, enabling the discovery of cross‐family co‐evolutionary networks and population‐specific diversity.
Shuai Wang +5 more
wiley +1 more source
Physics-Based Inverse Modeling of Battery Degradation with Bayesian Methods. [PDF]
Philipp MCJ +3 more
europepmc +1 more source
Application of Bayesian methods to accelerate rare disease drug development: scopes and hurdles. [PDF]
Kidwell KM +9 more
europepmc +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Who benefits? Uncovering hidden heterogeneity of treatment effects in adaptive trials using Bayesian methods: a systematic review. [PDF]
Giblon R +7 more
europepmc +1 more source
A Statistical Mechanics Model to Decode Tissue Crosstalk During Graft Formation
We introduce a statistical mechanics framework to decode the genomic crosstalk governing plant grafting. By integrating evolutionary game theory with transcriptomics, we reconstruct idopNetworks (informative, dynamic, omnidirectional, and personalized networks) that map scion–rootstock interactions.
Ang Dong +4 more
wiley +1 more source

