Results 191 to 200 of about 25,216,828 (261)
Use of Automation Technologies and Data Mining in Speech Recognition for Autism. [PDF]
Mao R, Zhu Y.
europepmc +1 more source
Single‐cell host–bacterial 16S co‐sequencing (scH16S‐seq) integrates cell‐associated bacterial 16S‐derived signals with host transcriptomes to resolve bacterial signal‐enriched myeloid states in Klebsiella pneumoniae sepsis. Complementary pharmacological and genetic analyses define a CD38–NAD immunometabolic axis connecting mitochondrial bioenergetic ...
Yangguang Li +15 more
wiley +1 more source
Data mining revealed no other trinucleotide repeat expansion associated with the Huntington's disease biomarker (CAG). [PDF]
Alaqeeli O.
europepmc +1 more source
Flexible Integration of Structurally Diverse Spatial Multi‐Omics With AgaeSMO
AgaeSMO is a versatile and robust deep learning framework for flexible cross‐integration of spatial multi‐omics data. Leveraging a GATs network with a graph attention module, it learns joint embedding across diverse modalities, enabling integration of both structurally paired (e.g., spatial transcriptome‐epigenome, transcriptome‐proteome, transcriptome‐
Kunpeng Liu +9 more
wiley +1 more source
Evidence-based precision in TCM: A systematic review and Meta-Analysis of data mining for syndrome-specific acupoint combinations in acute asthma exacerbations. [PDF]
Yang S, Yang Y, Ding Y, Liu X.
europepmc +1 more source
A lactate‐H3K18la epigenetic axis upregulates RPL11 to drive gemcitabine resistance in pancreatic cancer. RPL11 orchestrates chemoresistance through a dual, compartmentalized role: enhancing cytoplasmic protein synthesis via EEF1A1 stabilization and promoting nuclear DNA damage repair by co‐activating PARP14, thus ensuring robust cell survival ...
Lijun Zhao +10 more
wiley +1 more source
ChIP-Atlas 2025 update: 10-year anniversary of a data-mining platform for exploring epigenomic landscape. [PDF]
Zou Z, Ohta T, Kasukawa T, Oki S.
europepmc +1 more source
LLM‐Assisted Design of Ultralow‐κ$\kappa$ Chalcogenides
An AI assisted, physics guided workflow accelerates the discovery of ultralow thermal conductivity materials by combining Bayesian optimization, evidence conditioned LLM reasoning, and automated physics‐based validation. The framework uncovers dynamically stable Ag based chalcogenides with ultralow thermal conductivity and promising thermoelectric ...
Yujie Liu +9 more
wiley +1 more source

