Results 111 to 120 of about 3,906,906 (309)

Probability Theory and Mathematical Statistics E-course in Nomotex DLS [PDF]

open access: diamond, 2020
Yu. I. Dimitrienko   +3 more
openalex   +1 more source

Spatiotemporal Characterization of the Functional MRI Latency Structure with Respect to Neural Signaling and Brain Hierarchy

open access: yesAdvanced Science, EarlyView.
Resting‐state fMRI captures intrinsic brain activity, yet the physical significance of latency structures remains unclear. In this study, the spatiotemporal properties of fMRI‐derived latency structures are examined by linking them to biophysical model‐based neural functions, intrinsic neural timescales, and functional gradients.
Hyoungshin Choi   +5 more
wiley   +1 more source

SCRIPT: Predicting Single‐Cell Long‐Range Cis‐Regulation Based on Pretrained Graph Attention Networks

open access: yesAdvanced Science, EarlyView.
SCRIPT is a novel method inferring single‐cell cis‐regulatory relationships (CRRs) from transcriptomic and chromatin accessibility data. SCRIPT incorporates two key innovations: graph causal attention networks supported by empirical CRR evidence, and representation learning enhanced through pretraining on atlas‐scale single‐cell data.
Yu Zhang   +13 more
wiley   +1 more source

Unveiling the Fundamental Principles of Reconfigurable Resistance States in Silver/Poly(Ethylene Glycol) Nanofluids

open access: yesAdvanced Science, EarlyView.
The electrophoretic reorganization of Ag nanoparticles within a poly(ethylene glycol) leads to the formation of conductive bridges with reconfigurable resistance states. Diverse conduction characteristics of the bridge range between ohmic conduction, nonlinear tunneling, or space charge‐limited conduction, and high resistance states.
Daniil Nikitin   +19 more
wiley   +1 more source

SGCD: High‐Resolution Spatial Domain Characterization via Data Interpolation and Cell‐Type Deconvolution

open access: yesAdvanced Science, EarlyView.
SGCD presents a novel approach for tissue spatial domain identification by employing interpolation to estimate inter‐spot gene expression and deconvolution to resolve cell‐type composition in both sampled and interstitial regions. By integrating gene expression, cell type, and spatial coordinates within a graph contrastive learning framework, SGCD ...
Tianjiao Zhang   +7 more
wiley   +1 more source

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