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   Articles with "deep graph" as a keyword



A Unified Deep Graph Model for Identifying the Molecular Categories of Ligands Targeting Nuclear Receptors

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recommendations! Published in 2025 at "Journal of chemical information and modeling"

DOI: 10.1021/acs.jcim.5c00700

Abstract: To fulfill functions for differentially regulating the downstream signaling pathways, functional ligands (i.e., agonists or antagonists) targeting nuclear receptors (NRs) are designed to stabilize different conformations (active or inactive) of the proteins. However, in practical… read more here.

Keywords: deep graph; unified deep; nuclear receptors; model ... See more keywords

Predicting Lattice Vibrational Frequencies Using Deep Graph Neural Networks

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recommendations! Published in 2022 at "ACS Omega"

DOI: 10.1021/acsomega.2c02765

Abstract: Lattice vibrational frequencies are related to many important materials properties such as thermal and electrical conductivity as well as superconductivity. However, computational calculation of vibrational frequencies using density functional theory methods is computationally too demanding… read more here.

Keywords: deep graph; vibrational frequencies; lattice vibrational; graph neural ... See more keywords

AFSE: towards improving model generalization of deep graph learning of ligand bioactivities targeting GPCR proteins.

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recommendations! Published in 2022 at "Briefings in bioinformatics"

DOI: 10.1093/bib/bbac077

Abstract: Ligand molecules naturally constitute a graph structure. Recently, many excellent deep graph learning (DGL) methods have been proposed and used to model ligand bioactivities, which is critical for the virtual screening of drug hits from… read more here.

Keywords: graph learning; generalization; ligand; model ... See more keywords

Dynamic LEO Satellite Routing Approach Based on Deep Graph Attention and Incremental Evolutionary Reinforcement Learning

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recommendations! Published in 2025 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2025.3607492

Abstract: Low Earth orbit (LEO) satellite networks are an important component of future 6G. However, due to the unique characteristics of the space environment—such as the complexity in modeling network states and the rapid dynamics of… read more here.

Keywords: based deep; satellite; deep graph; attention ... See more keywords

GraphPLBR: Protein-ligand Binding Residue Prediction with Deep Graph Convolution Network.

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recommendations! Published in 2023 at "IEEE/ACM transactions on computational biology and bioinformatics"

DOI: 10.1109/tcbb.2023.3239983

Abstract: The intermolecular interactions between proteins and ligands occur through site-specific amino acid residues in the proteins, and the identification of these key residues plays a critical role in both interpreting protein function and facilitating drug… read more here.

Keywords: deep graph; ligand binding; prediction; binding residues ... See more keywords

PANDORA: Deep Graph Learning Based COVID-19 Infection Risk Level Forecasting

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recommendations! Published in 2024 at "IEEE Transactions on Computational Social Systems"

DOI: 10.1109/tcss.2022.3229671

Abstract: Coronavirus disease 2019 (COVID-19) as a global pandemic causes a massive disruption to social stability that threatens human life and the economy. An effective forecasting system is arguably important to provide an early signal of… read more here.

Keywords: deep graph; covid infection; risk; infection ... See more keywords

Deep Graph Reinforcement Learning for UAV-Enabled Multi-User Secure Communications

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recommendations! Published in 2025 at "IEEE Transactions on Mobile Computing"

DOI: 10.1109/tmc.2025.3558790

Abstract: While unmanned aerial vehicles(UAVs) with flexible mobility are envisioned to enhance physical layer security in wireless communications, the efficient security design that adapts to such high network dynamics is rather challenging. The conventional approaches extended… read more here.

Keywords: security; uav enabled; deep graph; reinforcement learning ... See more keywords
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Explaining Deep Graph Networks via Input Perturbation.

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recommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2022.3165618

Abstract: Deep graph networks (DGNs) are a family of machine learning models for structured data which are finding heavy application in life sciences (drug repurposing, molecular property predictions) and on social network data (recommendation systems). The… read more here.

Keywords: deep graph; via input; networks via; explaining deep ... See more keywords
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Deep Graph Metric Learning for Weakly Supervised Person Re-Identification.

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recommendations! Published in 2021 at "IEEE transactions on pattern analysis and machine intelligence"

DOI: 10.1109/tpami.2021.3084613

Abstract: In conventional person re-identification (re-id), the images used for model training in the training probe set and training gallery set are all assumed to be instance-level samples. This labeling across multiple non-overlapping camera views from… read more here.

Keywords: person; video; deep graph; supervised person ... See more keywords

Self-taught hashing using deep graph embedding for large-scale image retrieval

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recommendations! Published in 2020 at "Journal of Electronic Imaging"

DOI: 10.1117/1.jei.29.3.033014

Abstract: Abstract. Existing deep hashing algorithms fail to achieve satisfactory results from unseen data owing to the out-of-sample problem. Graph-embedding-based hashing methods alleviate this by learning the distance between samples. However, they focus on the first-order… read more here.

Keywords: deep graph; self taught; using deep; image ... See more keywords

A Deep Graph-Embedded LSTM Neural Network Approach for Airport Delay Prediction

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recommendations! Published in 2021 at "Journal of Advanced Transportation"

DOI: 10.1155/2021/6638130

Abstract: Due to the strong propagation causality of delays between airports, this paper proposes a delay prediction model based on a deep graph neural network to study delay prediction from the perspective of an airport network.… read more here.

Keywords: delay prediction; delay; deep graph; network ... See more keywords