Results 201 to 210 of about 101,551 (301)

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

open access: yesAdvanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu   +5 more
wiley   +1 more source

Reply to Arroyo et al.: Universality and diversity in thermal performance curves. [PDF]

open access: yesProc Natl Acad Sci U S A
Arnoldi JF   +3 more
europepmc   +1 more source

Electrohydraulic Folding Ring Actuators for Radially Contracting Applications

open access: yesAdvanced Science, EarlyView.
This work presents an Electrohydraulic Folding Ring Actuator that combines high‐performance electrohydraulic actuation with origami‐inspired folding geometry to achieve constricting radial actuation. This integration yields significant inner lumen constriction, alongside a gripping force capable of holding objects exceeding four times the actuator's ...
Gavril Yong En Tan   +4 more
wiley   +1 more source

Xue model exploration for oxytactic microbes in radiative MHD hybrid nanoliquid using machine learning technique. [PDF]

open access: yesDiscov Nano
Shaaban SM   +6 more
europepmc   +1 more source

In Vivo Electrochemical Monitoring of Safinamide Pharmacokinetics in the Brain Explores Its Correlation With Vision‐Related Neuronal Activity

open access: yesAdvanced Science, EarlyView.
An electrochemical platform based on differential pulse amperometry enables real‐time, selective tracking of safinamide pharmacokinetics in the living brain with high spatiotemporal resolution. When integrated with electrophysiology, this approach reveals that drug‐induced suppression of vision‐related neuronal activity provides mechanistic insight ...
Xiaoke Nan   +9 more
wiley   +1 more source

Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction

open access: yesAdvanced Science, EarlyView.
We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen   +3 more
wiley   +1 more source

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

open access: yesAdvanced Science, EarlyView.
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley   +1 more source

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