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Graph neural networks (GNNs) have been used extensively for addressing problems in drug design and discovery.
Labeled Graph Generative Adversarial Networks
Shuangfei Fan and Bert Huang · 1906
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Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms
Michael Perlmutter, Feng Gao, Guy Wolf, and Matthew Hirn · 1911
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GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, and Jian Tang · 2001
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ZINC – A Free Database of Commercially Available Compounds for Virtual Screening
John J. Irwin and Brian K. Shoichet · 2005
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Diffusion wavelets
Ronald R. Coifman and Mauro Maggioni · 2006
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Diffusion maps
Ronald R. Coifman and Stéphane Lafon · 2006
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Autoencoder Image Interpolation by Shaping the Latent Space
Alon Oring, Zohar Yakhini, and Yacov Hel-Or · 2008
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Data-Driven Learning of Geometric Scattering Networks
Alexander Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, and Guy Wolf · 2010
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Group invariant scattering
Stéphane Mallat · 2012
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Quantifying the chemical beauty of drugs
G. Richard Bickerton, Gaia V. Paolini, Jérémy Besnard, Sorel Muresan, and Andrew L. Hopkins · 2012
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Two- and Three-dimensional Rings in Drugs
Matteo Aldeghi, Shipra Malhotra, David L Selwood, and Ah Wing Edith Chan · 2014
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ChEMBL web services: streamlining access to drug discovery data and utilities
Mark Davies, Michał Nowotka, George Papadatos, Nathan Dedman, Anna Gaulton, Francis Atkinson, Louisa Bellis, and John P. Overington · 2015
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Diffusion pseudotime robustly reconstructs lineage branching
Laleh Haghverdi, Maren Büttner, F Alexander Wolf, Florian Buettner, and Fabian J Theis · 2016
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BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology
Michael K. Gilson, Tiqing Liu, Michael Baitaluk, George Nicola, Linda Hwang, and Jenny Chong · 2016
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Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf and Max Welling · 2017
Graph transformer networks
Seongjun Yun, Minbyul Jeong, Raehyun Kim, Jaewoo Kang, and Hyunwoo J Kim · 2019
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Visualizing structure and transitions in high-dimensional biological data
Kevin R. Moon, David van Dijk, Zheng Wang, Scott Gigante, Daniel B. Burkhardt, William S. Chen, Kristina Yim, Antonia van den Elzen, Matthew J. Hirn, Ronald R. Coifman, Natalia B. Ivanova, Guy Wolf, and Smita Krishnaswamy · 2019
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Geometric scattering for graph data analysis
Feng Gao, Guy Wolf, and Matthew Hirn · 2019
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Stability of graph scattering transforms
Fernando Gama, Alejandro Ribeiro, and Joan Bruna · 2019
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Encoding robust representation for graph generation
Dongmian Zou and Gilad Lerman · 2019
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Graph convolutional neural networks via scattering
Dongmian Zou and Gilad Lerman · 2020
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David van Dijk, Juozas Nainys, Roshan Sharma, Pooja Kaithail, Ambrose J Carr, Kevin R Moon, Linas Mazutis, Guy Wolf, Smita Krishnaswamy, and Dana Pe’er · 2017
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MolGAN: An implicit generative model for small molecular graphs
Nicola De Cao and Thomas Kipf · 2018
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Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
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Diffusion scattering transforms on graphs
Fernando Gama, Alejandro Ribeiro, and Joan Bruna · 2018
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Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing
Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, and Aram Galstyan · 2019
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Scattering GCN: Overcoming oversmoothness in graph convolutional networks
Yimeng Min, Frederik Wenkel, and Guy Wolf · 2020
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Uncovering the folding landscape of RNA secondary structure using deep graph embeddings
Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, and Smita Krishnaswamy · 2020
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Geometric scattering attention networks
Yimeng Min, Frederik Wenkel, and Guy Wolf · 2021
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