Results 261 to 270 of about 804,912 (360)

SAGE: Spatially Aware Gene Selection and Dual‐View Embedding Fusion for Domain Identification in Spatial Transcriptomics

open access: yesAdvanced Science, EarlyView.
SAGE is a unified framework for spatial domain identification in spatial transcriptomics that jointly models tissue architecture and gene programs. Topic‐driven gene selection (NMF plus classifier‐based scoring) highlights spatially informative genes, while dual‐view graph embedding fuses local expression and non‐local functional relations.
Yi He   +5 more
wiley   +1 more source

Reconstructing Coherent Functional Landscape From Multi‐Modal Multi‐Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process

open access: yesAdvanced Science, EarlyView.
This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang   +3 more
wiley   +1 more source

Pattern separation in the hippocampus

open access: yesTrends in Neurosciences, 2011
M. Yassa, C. Stark
semanticscholar   +1 more source

Dorsal Raphe VIP Neurons Are Critical for Survival‐Oriented Vigilance

open access: yesAdvanced Science, EarlyView.
DRNVIP neurons in mice and primates are strategically positioned to influence the central extended amygdala via feedback loops. They regulate the excitability of PKC‐δ neurons in the ovBNST and CeA through glutamate release. Their ablation heightens activity in these regions, disrupts active‐phase sleep architecture, enhances risk assessment behaviors ...
Adriane Guillaumin   +15 more
wiley   +1 more source

Dopamine release from the locus coeruleus to the dorsal hippocampus promotes spatial learning and memory

open access: yesProceedings of the National Academy of Sciences of the United States of America, 2016
Kimberly A. Kempadoo   +4 more
semanticscholar   +1 more source

Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

open access: yesAdvanced Intelligent Discovery, EarlyView.
A multimodal fusion pipeline predicts high‐resolution ion distributions in imaging mass spectrometry by integrating Fourier transform ion cyclotron resonance, time‐of‐flight matrix‐assisted laser desorption/ionization, and time‐of‐flight secondary ion mass spectrometry data.
Md Inzamam Ul Haque   +7 more
wiley   +1 more source

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