Results 101 to 110 of about 199,039 (272)

DualPG‐DTA: A Large Language Model‐Powered Graph Neural Network Framework for Enhanced Drug‐Target Affinity Prediction and Discovery of Novel CDK9 Inhibitors Exhibiting in Vivo Anti‐Leukemia Activity

open access: yesAdvanced Science, EarlyView.
This study introduces DualPG‐DTA, a framework integrating two pre‐trained models to generate molecular and protein representations. It constructs dual graphs processed by specialized neural networks with dynamic attention for feature fusion, achieving superior benchmark performance.
Yihao Chen   +7 more
wiley   +1 more source

S3RL: Enhancing Spatial Single‐Cell Transcriptomics With Separable Representation Learning

open access: yesAdvanced Science, EarlyView.
Separable Spatial Representation Learning (S3RL) is introduced to enhance the reconstruction of spatial transcriptomic landscapes by disentangling spatial structure and gene expression semantics. By integrating multimodal inputs with graph‐based representation learning and hyperspherical prototype modeling, S3RL enables high‐fidelity spatial domain ...
Laiyi Fu   +6 more
wiley   +1 more source

Bayesian optimized CNN ensemble for efficient potato blight detection using fuzzy image enhancement

open access: yesScientific Reports
Potato blight is a serious disease that affects potato crops and leads to substantial agricultural and economic losses. To enhance detection accuracy, we propose Bayesian Optimized CNN Weighted Ensemble Potato Blight Detection, a deep learning-based ...
Achin Jain   +12 more
doaj   +1 more source

Modification Strategies of Carbon‐Based Electrodes From Structural Regulation to Multifunctional Integration

open access: yesAdvanced Science, EarlyView.
Tracing the evolution from structural regulation to multifunctional integration, this paper systematically analyzes modification strategies for carbon‐based electrodes. It evaluates how element doping, surface functionalization, and composite material design affect the electrode performance, and offers perspectives on future applications and challenges
Yunlei Wang   +4 more
wiley   +1 more source

Nanozymes Integrated Biochips Toward Smart Detection System

open access: yesAdvanced Science, EarlyView.
This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen   +10 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

SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics

open access: yesAdvanced Science, EarlyView.
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao   +11 more
wiley   +1 more source

Benchmarking uncertainty quantification for protein engineering.

open access: yesPLoS Computational Biology
Machine learning sequence-function models for proteins could enable significant advances in protein engineering, especially when paired with state-of-the-art methods to select new sequences for property optimization and/or model improvement. Such methods
Kevin P Greenman   +2 more
doaj   +1 more source

Explicitly Bayesian Regularizations in Deep Learning

open access: yes, 2019
Generalization is essential for deep learning. In contrast to previous works claiming that Deep Neural Networks (DNNs) have an implicit regularization implemented by the stochastic gradient descent, we demonstrate explicitly Bayesian regularizations in a specific category of DNNs, i.e., Convolutional Neural Networks (CNNs).
Lan, Xinjie, Barner, Kenneth E.
openaire   +2 more sources

A Subset of Pro‐inflammatory CXCL10+ LILRB2+ Macrophages Derives From Recipient Monocytes and Drives Renal Allograft Rejection

open access: yesAdvanced Science, EarlyView.
This study uncovers a recipient‐derived monocyte‐to‐macrophage trajectory that drives inflammation during kidney transplant rejection. Using over 150 000 single‐cell profiles and more than 850 biopsies, the authors identify CXCL10+ macrophages as key predictors of graft loss.
Alexis Varin   +16 more
wiley   +1 more source

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