Articles with "graph matching" as a keyword



Pre‐Training of Equivariant Graph Matching Networks with Conformation Flexibility for Drug Binding

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Published in 2022 at "Advanced Science"

DOI: 10.1002/advs.202203796

Abstract: The latest biological findings observe that the motionless “lock‐and‐key” theory is not generally applicable and that changes in atomic sites and binding pose can provide important information for understanding drug binding. However, the computational expenditure… read more here.

Keywords: equivariant graph; graph matching; matching networks; drug binding ... See more keywords
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Ranking docking poses by graph matching of protein–ligand interactions: lessons learned from the D3R Grand Challenge 2

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Published in 2017 at "Journal of Computer-Aided Molecular Design"

DOI: 10.1007/s10822-017-0046-1

Abstract: A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the… read more here.

Keywords: challenge; poses graph; method; graph matching ... See more keywords

SymmPi: Exploiting Symmetry Removal for Fast Subgraph Matching

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Published in 2025 at "Data Science and Engineering"

DOI: 10.1007/s41019-024-00271-w

Abstract: Symmetry, a phenomenon of self-similarity, is common in many networks, which often incurs a lot of redundant accesses and computations, even duplicate results when executing graph matching tasks. Many approaches (e.g. symmetry-breaking methods) try to… read more here.

Keywords: symmetry removal; graph matching; symmetry; removal fast ... See more keywords

A novel method for graph matching based on belief propagation

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Published in 2019 at "Neurocomputing"

DOI: 10.1016/j.neucom.2018.10.018

Abstract: Abstract Graph matching is a fundamental NP-problem in computer vision and pattern recognition. In this paper, we propose a robust approximate graph matching method. The match between two graphs is formulated as an optimization problem… read more here.

Keywords: graph; graph matching; novel method; belief propagation ... See more keywords

HOGMMNC: a higher order graph matching with multiple network constraints model for gene‐drug regulatory modules identification

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Published in 2019 at "Bioinformatics"

DOI: 10.1093/bioinformatics/bty662

Abstract: Motivation: The emergence of large amounts of genomic, chemical, and pharmacological data provides new opportunities and challenges. Identifying gene‐drug associations is not only crucial in providing a comprehensive understanding of the molecular mechanisms of drug… read more here.

Keywords: higher order; gene drug; drug; order graph ... See more keywords

Progressively Decomposing Graph Matching

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Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2908925

Abstract: Existing approaches to graph matching mainly include two types, i.e., the Koopmans-Beckmann’s QAP formulation (KB-QAP) and Lawler’s QAP formulation (L-QAP). The former is advantageous in scalability but disadvantageous in generality, while the latter is exactly… read more here.

Keywords: progressively decomposing; method; qap; graph ... See more keywords

Identify Multiple Gene-Drug Common Modules via Constrained Graph Matching

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Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"

DOI: 10.1109/jbhi.2022.3188503

Abstract: Identifying gene-drug interactions is vital to understanding biological mechanisms and achieving precise drug repurposing. High-throughput technologies produce a large amount of pharmacological and genomic data, providing an opportunity to explore the associations between oncogenic genes… read more here.

Keywords: drug common; common modules; gene drug; graph matching ... See more keywords

Deep Graph Matching Based Dense Correspondence Learning Between Non-Rigid Point Clouds

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Published in 2022 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2022.3160237

Abstract: Building point-to-point dense correspondence between non-rigid shapes is a fundamental and challenging problem. Although functional map-based methods which calculate basis and convert point-wise map to functional map have shown promising performance on meshes, they are… read more here.

Keywords: non rigid; point clouds; graph matching; correspondence ... See more keywords

SemanticLoop: Loop Closure With 3D Semantic Graph Matching

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Published in 2022 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2022.3229228

Abstract: Loop closure can effectively correct the accumulated error in robot localization, which plays a critical role in the long-term navigation of the robot. Traditional appearance-based methods rely on local features and are prone to failure… read more here.

Keywords: closure; graph matching; loop closure; object level ... See more keywords

Radio Resource Management for C-V2X Using Graph Matching and Actor–Critic Learning

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Published in 2022 at "IEEE Wireless Communications Letters"

DOI: 10.1109/lwc.2022.3213176

Abstract: We propose a hybrid centralized-distributed radio resource management (RRM) scheme for cellular vehicle-to-everything (C-V2X), which is to mitigate the interference caused by radio resource sharing between vehicle-to-infrastructure (V2I) links and vehicle-to-vehicle (V2V) links. Specifically, it… read more here.

Keywords: resource management; critic learning; resource; graph matching ... See more keywords
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DeepSeed Local Graph Matching for Densely Packed Cells Tracking

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Published in 2021 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"

DOI: 10.1109/tcbb.2019.2936851

Abstract: The tracking of densely packed plant cells across microscopy image sequences is very challenging, because their appearance change greatly over time. A local graph matching algorithm was proposed to track such cells by exploiting the… read more here.

Keywords: local graph; image sequences; cell; graph matching ... See more keywords