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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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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cmdc.200900243openalex-snapshot
Molecular Fingerprint Recombination: Generating Hybrid Fingerprints for Similarity Searching from Different Fingerprint Types
inferredcites →https://doi.org/10.1002/qsar.200610084openalex-snapshot
Enhancing the Effectiveness of Ligand‐Based Virtual Screening Using Data Fusion
inferredcites →https://doi.org/10.1007/3-540-45984-7_6openalex-snapshot
Combining Decision Trees and Neural Networks for Drug Discovery
inferredcites →https://doi.org/10.1007/978-1-4419-9326-7openalex-snapshot
Ensemble Machine Learning: Methods and Applications
inferredcites →https://doi.org/10.1007/978-1-4612-2404-4openalex-snapshot
Learning from Data: Artificial Intelligence and Statistics V
inferredcites →https://doi.org/10.1007/s10822-008-9189-4openalex-snapshot
Community benchmarks for virtual screening
inferredcites →https://doi.org/10.1016/j.cbpa.2005.03.002openalex-snapshot
There is no such thing as ‘diversity’!
inferredcites →https://doi.org/10.1016/j.inffus.2010.05.002openalex-snapshot
A representative bibliography of surveys in the information fusion domain
inferredcites →https://doi.org/10.1016/j.neucom.2005.12.014openalex-snapshot
Evolving hybrid ensembles of learning machines for better generalisation
inferredcites →https://doi.org/10.1016/s0031-3203(99)00223-xopenalex-snapshot
Decision templates for multiple classifier fusion: an experimental comparison
inferredcites →https://doi.org/10.1016/s1359-6446(02)02411-xopenalex-snapshot
Why do we need so many chemical similarity search methods?
inferredcites →https://doi.org/10.1021/ci000397qopenalex-snapshot
Prediction of Biological Activity for High-Throughput Screening Using Binary Kernel Discrimination
inferredcites →https://doi.org/10.1021/ci00046a002openalex-snapshot
Atom pairs as molecular features in structure-activity studies: definition and applications
inferredcites →https://doi.org/10.1021/ci00054a008openalex-snapshot
Topological torsion: a new molecular descriptor for SAR applications. Comparison with other descriptors
inferredcites →https://doi.org/10.1021/ci034160gopenalex-snapshot
Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling
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/ci049867xopenalex-snapshot
Enhancing the Effectiveness of Virtual Screening by Fusing Nearest Neighbor Lists: A Comparison of Similarity Coefficients
inferredcites →https://doi.org/10.1021/ci0498719openalex-snapshot
Similarity Searching of Chemical Databases Using Atom Environment Descriptors (MOLPRINT 2D): Evaluation of Performance
inferredcites →https://doi.org/10.1021/ci049875dopenalex-snapshot
A Comparative Study on Feature Selection Methods for Drug Discovery
inferredcites →https://doi.org/10.1021/ci200199uopenalex-snapshot
Large-Scale Similarity Search Profiling of ChEMBL Compound Data Sets
inferredcites →https://doi.org/10.1021/ci2004994openalex-snapshot
Activity-Aware Clustering of High Throughput Screening Data and Elucidation of Orthogonal Structure–Activity Relationships
inferredcites →https://doi.org/10.1021/ci200615hopenalex-snapshot
Comparison of Random Forest and Pipeline Pilot Naïve Bayes in Prospective QSAR Predictions
inferredcites →https://doi.org/10.1021/ci300547gopenalex-snapshot
Combination of Similarity Rankings Using Data Fusion
inferredcites →https://doi.org/10.1021/ci4000536openalex-snapshot
Oversampling to Overcome Overfitting: Exploring the Relationship between Data Set Composition, Molecular Descriptors, and Predictive Modeling Methods
inferredcites →https://doi.org/10.1021/ci700461sopenalex-snapshot
Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds
inferredcites →https://doi.org/10.1021/ci800164uopenalex-snapshot
Practical Outcomes of Applying Ensemble Machine Learning Classifiers to High-Throughput Screening (HTS) Data Analysis and Screening
inferredcites →https://doi.org/10.1021/ci8002649openalex-snapshot
Maximum Unbiased Validation (MUV) Data Sets for Virtual Screening Based on PubChem Bioactivity Data
inferredcites →https://doi.org/10.1021/ci950274jopenalex-snapshot
Chemical Similarity Using Physiochemical Property Descriptors
inferredcites →https://doi.org/10.1021/ci950275bopenalex-snapshot
Chemical Similarity Using Geometric Atom Pair Descriptors
inferredcites →https://doi.org/10.1021/ci960466uopenalex-snapshot
Similarity Searching in Files of Three-Dimensional Chemical Structures: Evaluation of the EVA Descriptor and Combination of Rankings Using Data Fusion
inferredcites →https://doi.org/10.1023/a:1008752200506openalex-snapshot
Combination of molecular similarity measures using data fusion
inferredcites →https://doi.org/10.1039/b409865jopenalex-snapshot
Comparison of topological descriptors for similarity-based virtual screening using multiple bioactive reference structures
inferredcites →https://doi.org/10.1093/nar/gkr777openalex-snapshot
ChEMBL: a large-scale bioactivity database for drug discovery
inferredcites →https://doi.org/10.1109/5.554205openalex-snapshot
An introduction to multisensor data fusion
inferredcites →https://doi.org/10.1109/ijcnn.2006.1716517openalex-snapshot
Investigation on Diversity in Homogeneous and Heterogeneous Ensembles
inferredcites →https://doi.org/10.1142/s0218001403002897openalex-snapshot
COMBINATION, COOPERATION AND SELECTION OF CLASSIFIERS: A STATE OF THE ART
inferredcites →https://doi.org/10.1177/002029400103400802openalex-snapshot
Data Fusion by Intelligent Classifier Combination
inferredcites →https://doi.org/10.1186/1758-2946-1-14openalex-snapshot
Optimal assignment methods for ligand-based virtual screening
inferredcites →https://doi.org/10.1186/1758-2946-3-s1-o3openalex-snapshot
Making sure there's a "give" associated with the "take": producing and using open-source software in big pharma
inferredcites →https://doi.org/10.1186/1758-2946-5-26openalex-snapshot
Open-source platform to benchmark fingerprints for ligand-based virtual screening
inferredcites →https://doi.org/10.1517/17460441.2010.517832openalex-snapshot
How similar are those molecules after all? Use two descriptors and you will have three different answers
inferredcites →https://doi.org/10.2174/138620709788167962openalex-snapshot
Performance of Machine Learning Methods for Ligand-Based Virtual Screening
inferredcites →https://doi.org/10.2174/157489310794072508openalex-snapshot
A Review of Ensemble Methods in Bioinformatics
inferredcites →https://doi.org/10.2307/1932409openalex-snapshot
Measures of the Amount of Ecologic Association Between Species
inferredcites →https://doi.org/10.3233/ida-2005-9602openalex-snapshot
Selective fusion of heterogeneous classifiers
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-1-4939-7465-8_11openalex-snapshot
Methods for Virtual Screening of GPCR Targets: Approaches and Challenges
inferred← citeshttps://doi.org/10.1007/s00521-019-04462-9openalex-snapshot
Reconciling predictive and interpretable performance in repeat buyer prediction via model distillation and heterogeneous classifiers fusion
inferred← citeshttps://doi.org/10.1007/s10822-016-9959-3openalex-snapshot
ROCS-derived features for virtual screening
inferred← citeshttps://doi.org/10.1007/s11030-025-11184-9openalex-snapshot
Targeting Poly (ADP-ribose) polymerase-1 (PARP-1) for DNA repair mechanism through QSAR-based virtual screening and MD simulation
inferred← citeshttps://doi.org/10.1016/j.cell.2021.06.003openalex-snapshot
An Atlas of Protein-Protein Interactions Across Mouse Tissues
inferred← citeshttps://doi.org/10.1016/j.chembiol.2016.05.016openalex-snapshot
Evidence-Based and Quantitative Prioritization of Tool Compounds in Phenotypic Drug Discovery
inferred← citeshttps://doi.org/10.1016/j.chemolab.2021.104309openalex-snapshot
Efficient lipophilicity prediction of molecules employing deep-learning models
inferred← citeshttps://doi.org/10.1016/j.csbj.2023.01.013openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00204openalex-snapshot
Automated Identification of Chemical Series: Classifying like a Medicinal Chemist
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c00160openalex-snapshot
GHOST: Adjusting the Decision Threshold to Handle Imbalanced Data in Machine Learning
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c00715openalex-snapshot
Large-Scale Distributed Training of Transformers for Chemical Fingerprinting
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c00516openalex-snapshot
Machine Learning Pipeline for Molecular Property Prediction Using ChemXploreML
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00244openalex-snapshot
Data-Driven Derivation of an “Informer Compound Set” for Improved Selection of Active Compounds in High-Throughput Screening
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00572openalex-snapshot
Shared Consensus Machine Learning Models for Predicting Blood Stage Malaria Inhibition
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00778openalex-snapshot
Molecular Dynamics Fingerprints (MDFP): Machine Learning from MD Data To Predict Free-Energy Differences
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00249openalex-snapshot
Chemical Topic Modeling: Exploring Molecular Data Sets Using a Common Text-Mining Approach
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00315openalex-snapshot
Developing Collaborative QSAR Models Without Sharing Structures
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00616openalex-snapshot
Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00358openalex-snapshot
Evaluating Polymer Representations via Quantifying Structure–Property Relationships
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6b01611openalex-snapshot
Profiling Prediction of Kinase Inhibitors: Toward the Virtual Assay
inferred← citeshttps://doi.org/10.1021/acsmedchemlett.8b00488openalex-snapshot
Idea2Data: Toward a New Paradigm for Drug Discovery
inferred← citeshttps://doi.org/10.1021/acsomega.6c01630openalex-snapshot
Machine Learning-Assisted Discovery of Chiral Azobenzene Dopants for Liquid Crystals
inferred← citeshttps://doi.org/10.1021/ci500084wopenalex-snapshot
Global Quantitative Structure–Activity Relationship Models vs Selected Local Models as Predictors of Off-Target Activities for Project Compounds
inferred← citeshttps://doi.org/10.1021/ci500190popenalex-snapshot
Using Information from Historical High-Throughput Screens to Predict Active Compounds
inferred← citeshttps://doi.org/10.1021/ci500694copenalex-snapshot
Combinatorial Consensus Scoring for Ligand-Based Virtual Fragment Screening: A Comparative Case Study for Serotonin 5-HT3A, Histamine H1, and Histamine H4Receptors
inferred← citeshttps://doi.org/10.1038/s41598-021-89969-9openalex-snapshot
Data-science based analysis of perceptual spaces of odors in olfactory loss
inferred← citeshttps://doi.org/10.1039/d4dd00038bopenalex-snapshot
Graph neural networks for identifying protein-reactive compounds
inferred← citeshttps://doi.org/10.1088/2632-2153/ac99baopenalex-snapshot
Chemical transformer compression for accelerating both training and inference of molecular modeling
inferred← citeshttps://doi.org/10.1093/bib/bbab593openalex-snapshot
S2DV: converting SMILES to a drug vector for predicting the activity of anti-HBV small molecules
inferred← citeshttps://doi.org/10.1093/database/bav087openalex-snapshot
Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME
inferred← citeshttps://doi.org/10.1093/nar/gku1212openalex-snapshot
CFam: a chemical families database based on iterative selection of functional seeds and seed-directed compound clustering
inferred← citeshttps://doi.org/10.1101/2021.02.22.432316openalex-snapshot
Milk-Way Algorithm applied in Imbalanced Dataset
inferred← citeshttps://doi.org/10.1109/bibm.2015.7359792openalex-snapshot
Exploration of topological torsion fingerprints
inferred← citeshttps://doi.org/10.1109/cibcb.2016.7758111openalex-snapshot
Using Bayesian modeling on molecular fragments features for virtual screening
inferred← citeshttps://doi.org/10.1142/s2737416524500479openalex-snapshot
Graph-Based Bidirectional Transformer Decision Threshold Adjustment Algorithm for Class-Imbalanced Molecular Data
inferred← citeshttps://doi.org/10.1186/1758-2946-6-19openalex-snapshot
Condorcet and borda count fusion method for ligand-based virtual screening
inferred← citeshttps://doi.org/10.1186/s13321-016-0173-zopenalex-snapshot
Filtered circular fingerprints improve either prediction or runtime performance while retaining interpretability
inferred← citeshttps://doi.org/10.1186/s13321-020-00443-6openalex-snapshot
QSAR-derived affinity fingerprints (part 1): fingerprint construction and modeling performance for similarity searching, bioactivity classification and scaffold hopping
inferred← citeshttps://doi.org/10.1186/s13321-024-00894-1openalex-snapshot
Democratizing cheminformatics: interpretable chemical grouping using an automated KNIME workflow
inferred← citeshttps://doi.org/10.1186/s13321-025-01003-6openalex-snapshot
GESim: ultrafast graph-based molecular similarity calculation via von Neumann graph entropy
inferred← citeshttps://doi.org/10.12688/f1000research.11905.1openalex-snapshot
Virtual-screening workflow tutorials and prospective results from the Teach-Discover-Treat competition 2014 against malaria
inferred← citeshttps://doi.org/10.1517/17460441.2016.1117070openalex-snapshot
An overview of molecular fingerprint similarity search in virtual screening
inferred← citeshttps://doi.org/10.17760/d20254504openalex-snapshot
New domains in automatic mechanism generation
inferred← citeshttps://doi.org/10.3389/fphar.2015.00105openalex-snapshot
Understanding the foundations of the structural similarities between marketed drugs and endogenous human metabolites
inferred← citeshttps://doi.org/10.3389/fphar.2016.00266openalex-snapshot
MetMaxStruct: A Tversky-Similarity-Based Strategy for Analysing the (Sub)Structural Similarities of Drugs and Endogenous Metabolites
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