Results 131 to 140 of about 175,631 (262)

Biochemically Constrained Multi‐Omics Integration Reveals Protein–Metabolite Dependencies Across Diseases

Advanced Science, EarlyView.
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao, Na Zhou, Ruotong Liu, Xiaofei Li, Jian Li, Fuzhong Xue, Qingzhen Hou   +6 more
wiley   +1 more source

BraMARS: An Interpretable Histopathology‐Driven Deep Learning Model for Brain Metastasis Risk Stratification in Surgically Resected Limited‐Stage SCLC

Advanced Science, EarlyView.
This study presents BraMARS, an explainable deep learning model that estimates future brain metastasis risk in surgically resected limited‐stage small‐cell lung cancer using routine H&E‐stained whole‐slide images. By linking model‐attributed spatial histopathology with clinical outcomes and proteomic programs, BraMARS provides a biologically ...
Zijian Yang, Taolue Wang, Shilong Liu, Zicheng Zhang, Yibo Zhang, Fan Yang, Bo Yu, Shuaishuai Gao, Yu Chen, Lin Yang, Meng Zhou   +10 more
wiley   +1 more source

The Optimal Machine Learning-Based Missing Data Imputation for the Cox Proportional Hazard Model. [PDF]

Front Public Health, 2021
Guo CY, Yang YC, Chen YH.
europepmc   +1 more source

Oligosaccharides With Defined Glycosidic Bonds Shape Gut Microbial Succession and Metabolism Via Bond‐Specific Microbial Responders

Advanced Science, EarlyView.
Oligosaccharides with defined glycosidic bonds drive divergent gut microbial succession and shape unique metabolic profiles. Absolute time‐series profiling with Bayesian generalized Lotka–Volterra modeling identifies bond‐specific microbial responders, while monoculture validation and metaproteomics reveal linkage‐matched transport and cleavage modules.
Xiaoxuan Lu, Jiaqi Zou, Geng Han, Mengyao Zhao, Ting Luo, Xiangru Feng, Liangliang Zhu, Yijia Chen, Xiaoguo Ji, Jiayang Jin, Liming Zhao   +10 more
wiley   +1 more source

Evaluating Missing Data Imputation Strategies for Environmental Mixture Models: A Simulation Study and Applied Analysis. [PDF]

Data Sci Sci
Boafo YS, Mostafa S, Obeng-Gyasi E.
europepmc   +1 more source

Self-Training With Quantile Errors for Multivariate Missing Data Imputation for Regression Problems in Electronic Medical Records: Algorithm Development Study. [PDF]

JMIR Public Health Surveill, 2021
Gwon H, Ahn I, Kim Y, Kang HJ, Seo H, Cho HN, Choi H, Jun TJ, Kim YH.   +8 more
europepmc   +1 more source

Spatiotemporal Multi‐Omic Mapping Reveals Liver‐Muscle Metabolic Crosstalk in Cancer Cachexia

Advanced Science, EarlyView.
The interactive CCAtlas platform delineates cross‐species, spatiotemporal, and sex‐specific molecular dynamics and metabolic rewiring across organs during cancer cachexia. Hepatic Gamt downregulation curtails hepatic creatine synthesis to trigger systemic creatine insufficiency and consequent skeletal muscle atrophy in LLC tumour‐bearing mice ...
Zihan Tian, Qianyu Wang, Wenyan Gao, Xianfeng Li, Jiawen Fan, Xiaoliang Wu, Siqi Liu, Xiangdong Ming, Danna Yeerken, Mutian Shen, Qingjie Min, Qimin Zhan, Yan Wang   +12 more
wiley   +1 more source

Management insulin dosing for diabetes using a partially observable Markov decision process with missing data imputation. [PDF]

Sci Rep
Xiang J, Yu H, Luo L, Liu S.
europepmc   +1 more source

Temporal and Spatial Nearest Neighbor Values Based Missing Data Imputation in Wireless Sensor Networks. [PDF]

Sensors (Basel), 2021
Deng Y, Han C, Guo J, Sun L.
europepmc   +1 more source

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi‐Scale Information and Metric Learning Framework for scDNAm Data

Advanced Science, EarlyView.
MethyAnno enables robust and interpretable annotation of single‐cell DNA methylation data by integrating multi‐scale epigenetic information, bidirectional cross‐attention, and prototype‐based metric learning. The framework resolves rare and novel cell types across datasets while revealing cell‐type‐specific epigenetic signatures associated with disease
Yuhang Jia, Siyu Li, Songming Tang, Keju Gu, Shengquan Chen   +4 more
wiley   +1 more source