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Kernel Approach to Molecular Similarity Based on Iterative Graph Similarity

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Graph kernels for chemical informatics
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Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships. 4. Additional parameters for hydrophobic and dispersive interactions and their application for an automated superposition of certain naturally occurring nucleoside antibiotics
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Review of ring perception algorithms for chemical graphs
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Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification
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Molecular Query Language (MQL)A Context-Free Grammar for Substructure Matching
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Chemical Similarity Searching
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Kernels and Distances for Structured Data
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A survey of the Predictive Toxicology Challenge 2000–2001
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Protein function prediction via graph kernels
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Proceedings of the International Joint Conference on Neural Networks (IJCNN) 2005
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Algorithms for the Assignment and Transportation Problems
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Proceedings of the 22nd international conference on Machine learning - ICML '05
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Optimal assignment kernels for attributed molecular graphs
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Proceedings of the 23rd international conference on Machine learning - ICML '06
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Proceedings of the 25th international conference on Machine learning - ICML '08
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Advances in kernel methods: support vector learning

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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