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Fig. 2 | Journal of Cheminformatics

Fig. 2

From: MOFGalaxyNet: a social network analysis for predicting guest accessibility in metal–organic frameworks utilizing graph convolutional networks

Fig. 2

The workflow of constructing MOFGalaxyNet involves utilizing data pertaining to metals and linkers. To build this graph, information from the Metal Organic Framework table is employed, including linker details in SMILES format and metal properties. The PLD column in the table represents the specific property that we aim to predict using MOFGalaxyNet. MOFGalaxyNet functions as a social network that showcases the galaxies of MOFs, providing valuable insights into their characteristics and interactions. Social Network Analysis (SNA) serves as a machine learning technique employed to analyze the graph structure of MOFGalaxyNet. Additionally, the GCN node classification method is utilized to predict guest accessibility by leveraging the information contained within MOFGalaxyNet

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