Results 111 to 120 of about 235,639 (329)
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
Natural Variation of NAR5 Determines Nitrogenase Activity and the Yield in Soybean
This study identified NAR5, a gene encoding a subtilisin‐like protease, that regulates nitrogenase activity in soybean nodules. Overexpressing NAR5 delayed nodule senescence, enhancing nitrogenase activity, yield, and low‐nitrogen tolerance. The elite haplotype NAR5HapI‐1 linked to superior nitrogenase activity and greater seed weight has been ...
Chao Ma +11 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
Air conditioning reliability analysis based on dynamic Bayesian network and Markov model
With the popularization of the air conditioning, its reliability during operation has gradually become a focus of attention. However, due to the uncertainty in the reliability analysis process, the accuracy of the results will be affected.
Xu Jiaqi +5 more
doaj +1 more source
Gene regulatory network modeling via global optimization of high-order dynamic Bayesian network
Background Dynamic Bayesian network (DBN) is among the mainstream approaches for modeling various biological networks, including the gene regulatory network (GRN). Most current methods for learning DBN employ either local search such as hill-climbing, or
Xuan Nguyen +3 more
doaj +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
Infinite dynamic bayesian networks
United States. Air Force Office of Scientific Research (AFOSR FA9550-07-1-0075)
Doshi-Velez, Finale P. +3 more
openaire +1 more source
ABSTRACT The muscle capsule of Trichinella is a critical structure that impedes immune attacks and drug penetration, yet the molecular mechanisms underlying its formation remain poorly understood. Using a high‐quality super‐pangenome comprising 12 Trichinella species, we compared extensive genomic variations between encapsulating and non‐encapsulating ...
Qingbo Lv +8 more
wiley +1 more source
Fault diagnosis for mechanical system using dynamic Bayesian network
Tian Yang Pang, Tian Yu, Bi Feng Song
openalex +1 more source
The authors complement bovine pan‐SV with massive novel structural variations (SVs) identified through long‐read sequencing of 83 globally distributed cattle breeds. Repetitive sequence‐mediated SVs (rep‐SV) exhibit distinct dynamic patterns throughout cattle sub‐speciation and/or domestication processes, including uneven distribution between chr‐X and
Zhifan Guo +16 more
wiley +1 more source

