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Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cmdc.200600225openalex-snapshot
Comparison of 2D Fingerprint Methods for Multiple‐Template Similarity Searching on Compound Activity Classes of Increasing Structural Diversity
inferredcites →https://doi.org/10.1016/j.drudis.2006.10.005openalex-snapshot
Similarity-based virtual screening using 2D fingerprints
inferredcites →https://doi.org/10.1016/j.drudis.2007.01.011openalex-snapshot
Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches
inferredcites →https://doi.org/10.1016/j.neunet.2005.07.009openalex-snapshot
Graph kernels for chemical informatics
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Drug design by machine learning: support vector machines for pharmaceutical data analysis
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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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Selected Concepts and Investigations in Compound Classification, Molecular Descriptor Analysis, and Virtual Screening
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Similarity Metrics for Ligands Reflecting the Similarity of the Target Proteins
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Active Learning with Support Vector Machines in the Drug Discovery Process
inferredcites →https://doi.org/10.1021/ci030287uopenalex-snapshot
Profile Scaling Increases the Similarity Search Performance of Molecular Fingerprints Containing Numerical Descriptors and Structural Keys
inferredcites →https://doi.org/10.1021/ci0341161openalex-snapshot
Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification
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Molecular Similarity Searching Using Atom Environments, Information-Based Feature Selection, and a Naïve Bayesian Classifier
inferredcites →https://doi.org/10.1021/ci034231bopenalex-snapshot
Comparison of Fingerprint-Based Methods for Virtual Screening Using Multiple Bioactive Reference Structures
inferredcites →https://doi.org/10.1021/ci049641uopenalex-snapshot
Virtual Screening of Molecular Databases Using a Support Vector Machine
inferredcites →https://doi.org/10.1021/ci049714+openalex-snapshot
ZINC − A Free Database of Commercially Available Compounds for Virtual Screening
inferredcites →https://doi.org/10.1021/ci050397wopenalex-snapshot
Virtual Screening Using Binary Kernel Discrimination: Analysis of Pesticide Data
inferredcites →https://doi.org/10.1021/ci600303bopenalex-snapshot
Design and Evaluation of a Novel Class-Directed 2D Fingerprint to Search for Structurally Diverse Active Compounds
inferredcites →https://doi.org/10.1021/ci950169+openalex-snapshot
Stigmata: An Algorithm To Determine Structural Commonalities in Diverse Datasets
inferredcites →https://doi.org/10.1021/ci950275bopenalex-snapshot
Chemical Similarity Using Geometric Atom Pair Descriptors
inferredcites →https://doi.org/10.1021/ci960151eopenalex-snapshot
Clustering of Large Databases of Compounds: Using the MDL “Keys” as Structural Descriptors
inferredcites →https://doi.org/10.1021/ci990162iopenalex-snapshot
The Characterization of Chemical Structures Using Molecular Properties. A Survey
inferredcites →https://doi.org/10.1021/jm0582165openalex-snapshot
Searching Techniques for Databases of Two- and Three-Dimensional Chemical Structures
inferredcites →https://doi.org/10.1021/jm9806998openalex-snapshot
New 4-Point Pharmacophore Method for Molecular Similarity and Diversity Applications: Overview of the Method and Applications, Including a Novel Approach to the Design of Combinatorial Libraries Containing Privileged Substructures
inferredcites →https://doi.org/10.1038/nrd791openalex-snapshot
Combinatorial informatics in the post-genomics era
inferredcites →https://doi.org/10.1038/nrd941openalex-snapshot
Integration of virtual and high-throughput screening
inferredcites →https://doi.org/10.1109/72.914517openalex-snapshot
An introduction to kernel-based learning algorithms
inferredcites →https://doi.org/10.5555/299094openalex-snapshot
Advances in kernel methods: support vector learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Applied Virtual Screening: Strategies, Recommendations, and Caveats
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Similarity‐Based Virtual Screening Using Bayesian Inference Network: Enhanced Search Using 2D Fingerprints and Multiple Reference Structures
inferred← citeshttps://doi.org/10.1002/qsar.200960062openalex-snapshot
Bayesian Inference Network Significantly Improves the Effectiveness of Similarity Searching Using Multiple 2D Fingerprints and Multiple Reference Structures
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Similarity Searching Using 2D Structural Fingerprints
inferred← citeshttps://doi.org/10.1007/978-3-030-33582-3_25openalex-snapshot
Methods to Improve Ranking Chemical Structures in Ligand-Based Virtual Screening
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Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries
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Power Normalization for Mass Spectrometry Data Analysis and Analytical Method Assessment
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Characterization of Small Molecule Binding. I. Accurate Identification of Strong Inhibitors in Virtual Screening
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Heterogeneous Classifier Fusion for Ligand-Based Virtual Screening: Or, How Decision Making by Committee Can Be a Good Thing
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