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Protein complex formation is a central problem in biology, being involved in most of the cell's processes, and essential for applications, e.g.
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The cluspro web server for protein–protein docking
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Improved protein structure prediction using predicted interresidue orientations
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Accurate prediction of protein structures and interactions using a three-track neural network
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Deepbsp—a machine learning method for accurate prediction of protein–ligand docking structures
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Improved prediction of protein-protein interactions using alphafold2 and extended multiple-sequence alignments
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Lzerd webserver for pairwise and multiple protein–protein docking
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Confold2: Improved contact-driven ab initio protein structure modeling
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N. Thomas, T. Smidt, S. Kearnes, L. Yang, L. Li, K. Kohlhoff, and P. Riley · 2018
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How powerful are graph neural networks?
K. Xu, W. Hu, J. Leskovec, and S. Jegelka · 2018
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Generative models for graph-based protein design
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Graph matching networks for learning the similarity of graph structured objects
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Structures of core eukaryotic protein complexes
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Highly accurate protein structure prediction with alphafold
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Structure-aware interactive graph neural networks for the prediction of protein-ligand binding affinity
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Human mitochondrial protein complexes revealed by large-scale coevolution analysis and deep learning-based structure modeling
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