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One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties

https://doi.org/10.1021/ci600397p
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Graph Kernels for Molecular Structure−Activity Relationship Analysis with Support Vector Machines
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Effectiveness of graph-based and fingerprint-based similarity measures for virtual screening of 2D chemical structure databases
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Chemical space and biology
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Structure-based inhibitor design of AccD5, an essential acyl-CoA carboxylase carboxyltransferase domain of Mycobacterium tuberculosis
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Mismatch string kernels for discriminative protein classification
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Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity
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A training algorithm for optimal margin classifiers
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Three-dimensional alpha shapes
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LIBSVM
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Learning with Kernels

What points at this work

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

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One‐ to Four‐Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties.
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Probabilistic Modeling of Conformational Space for 3D Machine Learning Approaches
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