GNNkeras: A Keras-based library for Graph Neural Networks and homogeneous and heterogeneous graph processing

Grindley, 1993, Identification of tertiary structure resemblance in proteins using a maximal common subgraph isomorphism algorithm, J Mol Biol, 229, 707, 10.1006/jmbi.1993.1074 Gardiner, 1997, Clique–detection algorithms for matching three–dimensional molecular structures, J Mol Graph Model, 15, 245, 10.1016/S1093-3263(97)00089-2 Pancino Niccolò, Rossi Alberto, Ciano Giorgio, Giacomini Giorgia, Bonechi Simone, Andreini Paolo, Scarselli Franco, Bianchini Monica, Bongini Pietro. Graph Neural Networks for the Prediction of Protein–Protein Interfaces. In: Proceedings of the 28th european symposium on artificial neural networks, computational intelligence and machine learning, ESANN 2020, Bruges, Belgium, October 2–4; 2020, pp. 127–32. Zitnik, 2018, Modeling polypharmacy side effects with graph convolutional networks, Bioinformatics, 34, i457, 10.1093/bioinformatics/bty294 Scarselli, 2009, The graph neural network model, IEEE Trans Neural Netw, 20, 61, 10.1109/TNN.2008.2005605 Kipf, 2016 Hamilton William L, Ying Rex, Leskovec Jure. Inductive representation learning on large graphs. In: Proceedings of the 31st International Conference on Neural Information Processing Systems; 2017, pp. 1025–35. Veličković, 2017 Battaglia, 2018 Hsieh, 2021, Drug repurposing for covid–19 using graph neural network and harmonizing multiple evidence, Sci Rep, 11, 10.1038/s41598-021-02353-5 Sanchez-Gonzalez, 2020, Learning to simulate complex physics with graph networks, 119, 8459 Ying Rex, He Ruining, Chen Kaifeng, Eksombatchai Pong, Hamilton William L, Leskovec Jure. Graph convolutional neural networks for web–scale recommender systems. In: Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining; 2018, pp. 974–83. Zhou, 2020, Graph neural networks: A review of methods and applications, AI Open, 1, 57, 10.1016/j.aiopen.2021.01.001 Bacciu, 2020, A gentle introduction to deep learning for graphs, Neural Netw, 129, 203, 10.1016/j.neunet.2020.06.006 Wu, 2021, A comprehensive survey on graph neural networks, IEEE Trans Neural Netw Learn Syst, 32, 4, 10.1109/TNNLS.2020.2978386 Bandinelli, 2010, Learning long–term dependencies using layered graph neural networks, 1 Rossi, 2018, Inductive–transductive learning with graph neural networks, 201 Ciano, 2022, On inductive–transductive learning with graph neural networks, IEEE Trans Pattern Anal Mach Intell, 44, 758, 10.1109/TPAMI.2021.3054304 Abadi, 2015 Sato, 2020 D’Inverno, 2021 Bongini, 2021, Molecular generative graph neural networks for drug discovery, Neurocomputing, 450, 242, 10.1016/j.neucom.2021.04.039