Results 81 to 90 of about 288,690 (232)

SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics

Advanced Science, EarlyView.
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, Gaiqin Liu, Jingyi Xia, Runle Chen, Tong Wang, Xiaoling Yang, Ruiling Fang, Yanhong Luo, Ping Zeng, Hongmei Yu, Yanbo Zhang, Yuehua Cui   +11 more
wiley   +1 more source

Natural Variation of NAR5 Determines Nitrogenase Activity and the Yield in Soybean

Advanced Science, EarlyView.
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, Hanyu Zhao, Haojie Feng, Xulun Dong, Lin Chen, Mingliang Yang, Runyi Chen, Chengjun Lei, Chunyan Liu, Qingshan Chen, Dawei Xin, Jinhui Wang   +11 more
wiley   +1 more source

Machine‐Learning Microfluidic Minute‐Scale Microorganism Metrics Monitoring(M6)

Advanced Science, EarlyView.
ABSTRACT On‐site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol‐transmitted pathogens. Here, we report a rapid detection platform that integrates a Puri‐focusing microfluidic chip, electrochemical impedance spectroscopy (EIS), and ...
Ning Yang, Jiahao Ding, Si Chen, Lijie Yan, Shichao Ding, Lavonda Li, Junyi Sun, Haodong Liu, Tongge Li, Ning Liu, Mingji Wei, Xiaoyong Zhu, Xiaobo Zou, Shouqi Yuan, Xingcai Zhang   +14 more
wiley   +1 more source

Explainable Bayesian Optimization

Abstract Manual parameter tuning of cyber-physical systems is a common practice, but it is labor-intensive. Bayesian Optimization (BO) offers an automated alternative, yet its black-box nature reduces trust and limits human-BO collaborative system tuning. Experts struggle to interpret BO recommendations due to the lack of explanations.
Tanmay Chakraborty, Christian Wirth, Christin Seifert   +2 more
openaire   +2 more sources

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
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, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
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, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

The Trichinella Super‐Pangenome Reveals the Evolution of Encapsulation and Predicted Host–Parasite Protein Interactions

Advanced Science, EarlyView.
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, Yi Liu, Ning Xu, Xiao Zhang, Yaming Yang, Chengyao Li, Hanhai Mao, Mingyuan Liu, Xiaolei Liu   +8 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Direct Regret Optimization in Bayesian Optimization

CoRR
Bayesian optimization (BO) is a powerful paradigm for optimizing expensive black-box functions. Traditional BO methods typically rely on separate hand-crafted acquisition functions and surrogate models for the underlying function, and often operate in a myopic manner.
Fengxue Zhang, Yuxin Chen
openaire   +2 more sources

Design of Single‐Atom Nanozymes for Precision Treatment of Erectile Dysfunction with Integrated Single‐Cell RNA Sequencing and Machine Learning

Advanced Science, EarlyView.
It is innovatively utilized single‐cell RNA sequencing to explore the underlying causes of diabetes mellitus‐induced erectile dysfunction, followed by machine learning‐driven design of a single‐atom nanozyme (Fe‐DMOF) for precision treatment of erectile dysfunction.
Xiang Zhou, Xi Zhang, Sihan Chen, Mengchi Yu, Yilan Hu, Chi Gan, Xianghu Meng, Long Li, Ninghong Song   +8 more
wiley   +1 more source