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Local Structural Changes, Global Data Views: Graphical Substructure−Activity Relationship Trailing
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Chemoinformatics in Drug Discovery
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Navigating structure–activity landscapes
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Data structures and computational tools for the extraction of SAR information from large compound sets
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Similarity−Potency Trees: A Method to Search for SAR Information in Compound Data Sets and Derive SAR Rules
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The Scaffold Tree − Visualization of the Scaffold Universe by Hierarchical Scaffold Classification
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Structure−Activity Landscape Index: Identifying and Quantifying Activity Cliffs
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Computationally Efficient Algorithm to Identify Matched Molecular Pairs (MMPs) in Large Data Sets
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SAR Maps: A New SAR Visualization Technique for Medicinal Chemists
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Activity Landscape Representations for Structure−Activity Relationship Analysis
inferredcites →https://doi.org/10.1021/jm800867gopenalex-snapshot
Structure−Activity Relationship Anatomy by Network-like Similarity Graphs and Local Structure−Activity Relationship Indices
inferredcites →https://doi.org/10.1021/jm900107bopenalex-snapshot
Exploration of Structure−Activity Relationship Determinants in Analogue Series
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The Properties of Known Drugs. 1. Molecular Frameworks
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BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities
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Systematic Computational Analysis of Structure–Activity Relationships: Concepts, Challenges and Recent Advances
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Additional file 1 of Large-scale prediction of activity cliffs using machine and deep learning methods of increasing complexity
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New methods of multiscale chemical space analysis : visualization of structure-activity relationships and structural pattern extraction
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