Results 211 to 220 of about 102,063 (249)

Discovering subnetworks in SBML models. [PDF]

Bioinformatics
Hellerstein JL, Smith LP, Tatka LT, Andrews SS, Kochen MA, Sauro HM.   +5 more
europepmc   +1 more source

GNNGL-PPI: multi-category prediction of protein-protein interactions using graph neural networks based on global graphs and local subgraphs. [PDF]

BMC Genomics
Zeng X, Meng FF, Wen ML, Li SJ, Li Y.
europepmc   +1 more source

Query by Example: Semantic Traffic Scene Retrieval Using LLM-Based Scene Graph Representation. [PDF]

Sensors (Basel)
Tian Y, Carballo A, Li R, Thompson S, Takeda K.   +4 more
europepmc   +1 more source

TinkerModeller: An Efficient Tool for Building Biological Systems in Tinker Simulations. [PDF]

J Chem Theory Comput
Wang X, Liu H, Li Y, Li J, Li WL.
europepmc   +1 more source

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A Parallel Algorithm for Subgraph Isomorphism

Workshop on Graph Based Representations in Pattern Recognition, 2019
In different application fields, such as biology, databases, social networks and so on, graphs are a widely adopted structure to represent the data. In these fields, a relevant problem is the detection and the localization of structural patterns within very large graphs; such a problem, formalized as subgraph isomorphism, has been proven to be NP ...
Vincenzo Carletti, P. Foggia, Pierluigi Ritrovato, M. Vento, Vincenzo Vigilante   +4 more
semanticscholar   +4 more sources

Hybrid Utilization of Subgraph Isomorphism and Relational Graph Convolutional Networks for Analog Functional Grouping Annotation

Workshop on Machine Learning for CAD, 2023
A hybrid method is proposed that combines the subgraph isomorphism algorithm VF2 and a relational graph convolutional network (RGCN) model for the recognition and classification of functional pairs in an analog circuit at the device level.
Zhengfeng Wu, Isabel Song, Ioannis Savidis   +2 more
semanticscholar   +1 more source

SGSI – A Scalable GPU-Friendly Subgraph Isomorphism Algorithm

IEEE Transactions on Knowledge and Data Engineering, 2023
Due to the inherent hardness of subgraph isomorphism, the performance is often a bottleneck in various real-world applications. We address this by designing an efficient subgraph isomorphism algorithm leveraging features of GPU architecture. Existing GPU-
Li Zeng, Lei Zou, M. Tamer Ozsu
semanticscholar   +1 more source