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Screening for New Antidepressant Leads of Multiple Activities by Support Vector Machines

https://doi.org/10.1021/ci050301y
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What this work says

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

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Virtual Screening for Bioactive Molecules
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Handbook of Chemoinformatics
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Advances in neural information processing systems 7
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Strategies for producing faster acting antidepressants
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Drug Discovery Using Support Vector Machines. The Case Studies of Drug-likeness, Agrochemical-likeness, and Enzyme Inhibition Predictions
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Comparison of Linear and Nonlinear Classification Algorithms for the Prediction of Drug and Chemical Metabolism by Human UDP-Glucuronosyltransferase Isoforms
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Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification
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Virtual Screening of Molecular Databases Using a Support Vector Machine
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Ensemble Methods for Classification in Cheminformatics
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Comparison of 2 D Similarity and 3 D Superposition. Application to Searching a Conformational Drug Database
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Do Structurally Similar Molecules Have Similar Biological Activity?
inferredcites →https://doi.org/10.1021/jm0302795openalex-snapshot
Prediction of Biological Targets Using Probabilistic Neural Networks and Atom-Type Descriptors
inferredcites →https://doi.org/10.1021/jm0582165openalex-snapshot
Searching Techniques for Databases of Two- and Three-Dimensional Chemical Structures
inferredcites →https://doi.org/10.1080/00401706.1999.10485951openalex-snapshot
Statistical Learning Theory
inferredcites →https://doi.org/10.1093/protein/9.11.1063openalex-snapshot
An automated approach for clustering an ensemble of NMR-derived protein structures into conformationally related subfamilies
inferredcites →https://doi.org/10.1142/5589openalex-snapshot
Support Vector Machine in Chemistry

What points at this work

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

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Toxicity Pathways and Models: Mining for Potential Side Effects
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An integrated database of flavonoids
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Screening for New Antidepressant Leads of Multiple Activities by Support Vector Machines.
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Application of a Novel Ant Algorithm Termed Continuous Gridded in Aidded Drug Design
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A Virtual Screening Study of the 18 kDa Translocator Protein using Pharmacophore Models Combined with 3D‐QSAR Studies
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Identification of small molecule aggregators from large compound libraries by support vector machines
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Development of Ligand‐based Big Data Deep Neural Network Models for Virtual Screening of Large Compound Libraries
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Multistage virtual screening and identification of novel HIV-1 protease inhibitors by integrating SVM, shape, pharmacophore and docking methods
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A support vector machines approach for virtual screening of active compounds of single and multiple mechanisms from large libraries at an improved hit-rate and enrichment factor
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Virtual screening prediction of new potential organocatalysts for direct aldol reactions
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Identification of a Chlorogenic Ester as a Monoamine Oxidase (MAO-B) Inhibitor by Integrating “Traditional and Machine Learning” Virtual Screening and In Vitro as well as In Vivo Validation: A Lead against Neurodegenerative Disorders?
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Identification of New Fyn Kinase Inhibitors Using a FLAP-Based Approach
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Predictive Activity Profiling of Drugs by Topological-Fragment-Spectra-Based Support Vector Machines
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Evaluation of Virtual Screening Performance of Support Vector Machines Trained by Sparsely Distributed Active Compounds
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SVM Model for Virtual Screening of Lck Inhibitors
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Virtual Screening of Abl Inhibitors from Large Compound Libraries by Support Vector Machines
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Computational Studies of Epidermal Growth Factor Receptor: Docking Reliability, Three-Dimensional Quantitative Structure−Activity Relationship Analysis, and Virtual Screening Studies
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In silicopharmacology for drug discovery: applications to targets and beyond
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Metabonomics in cancer diagnosis: mass spectrometry-based profiling of urinary nucleosides from breast cancer patients
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