On the public citation graph

Gaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity

https://doi.org/10.1021/ci900406x
0 signed · 89 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1002/jps.1031openalex-snapshot
Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure–activity relationship (QSAR) with the Abraham descriptors
inferredcites →https://doi.org/10.1007/s10822-008-9193-8openalex-snapshot
Automatic QSAR modeling of ADME properties: blood–brain barrier penetration and aqueous solubility
inferredcites →https://doi.org/10.1007/s11095-008-9584-5openalex-snapshot
New Predictive Models for Blood–Brain Barrier Permeability of Drug-like Molecules
inferredcites →https://doi.org/10.1016/j.bmc.2008.01.017openalex-snapshot
A binary QSAR model for classification of hERG potassium channel blockers
inferredcites →https://doi.org/10.1016/s1359-6446(03)02827-7openalex-snapshot
In silico prediction of blood–brain barrier permeation
inferredcites →https://doi.org/10.1017/cbo9780511801389openalex-snapshot
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
inferredcites →https://doi.org/10.1021/ci000459copenalex-snapshot
Quantitative Structure−Activity Relationship Studies Using Gaussian Processes
inferredcites →https://doi.org/10.1021/ci034143ropenalex-snapshot
Spline-Fitting with a Genetic Algorithm: A Method for Developing Classification Structure−Activity Relationships
inferredcites →https://doi.org/10.1021/ci034205dopenalex-snapshot
Blood-Brain Barrier Permeation Models: Discriminating between Potential CNS and Non-CNS Drugs Including P-Glycoprotein Substrates
inferredcites →https://doi.org/10.1021/ci050135uopenalex-snapshot
Effect of Selection of Molecular Descriptors on the Prediction of Blood−Brain Barrier Penetrating and Nonpenetrating Agents by Statistical Learning Methods
inferredcites →https://doi.org/10.1021/ci600205gopenalex-snapshot
Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach
inferredcites →https://doi.org/10.1021/ci600312dopenalex-snapshot
Predicting Penetration Across the Blood-Brain Barrier from Simple Descriptors and Fragmentation Schemes
inferredcites →https://doi.org/10.1021/ci7000633openalex-snapshot
Gaussian Processes: A Method for Automatic QSAR Modeling of ADME Properties
inferredcites →https://doi.org/10.1021/ci700142copenalex-snapshot
A Probabilistic Approach to Classifying Metabolic Stability
inferredcites →https://doi.org/10.1021/ci9803381openalex-snapshot
Unsupervised Data Base Clustering Based on Daylight's Fingerprint and Tanimoto Similarity: A Fast and Automated Way To Cluster Small and Large Data Sets
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1109/72.883477openalex-snapshot
Variational Gaussian process classifiers
inferredcites →https://doi.org/10.1145/1656274.1656278openalex-snapshot
The WEKA data mining software
inferredcites →https://doi.org/10.5860/choice.36-5691openalex-snapshot
Encyclopedia of computational chemistry

What points at this work

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

inferred← citeshttps://doi.org/10.1002/9781118819586.ch10openalex-snapshot
In Silico Approaches to Address Compound Attrition
inferred← citeshttps://doi.org/10.1002/9783527645121.ch1openalex-snapshot
Current Modeling Methods Used in QSAR/QSPR
inferred← citeshttps://doi.org/10.1002/jat.2804openalex-snapshot
Chemoinformatics and chemical genomics: potential utility of in silico methods
inferred← citeshttps://doi.org/10.1002/minf.201100059openalex-snapshot
Visual Interpretation of Kernel‐Based Prediction Models
inferred← citeshttps://doi.org/10.1002/minf.201100070openalex-snapshot
From Hits to Leads: Challenges for the Next Phase of Machine Learning in Medicinal Chemistry
inferred← citeshttps://doi.org/10.1002/minf.201400144openalex-snapshot
In silico Prediction of Aqueous Solubility: a Comparative Study of Local and Global Predictive Models
inferred← citeshttps://doi.org/10.1007/978-3-642-24855-9_14openalex-snapshot
Multi-task Drug Bioactivity Classification with Graph Labeling Ensembles
inferred← citeshttps://doi.org/10.1007/s00894-019-4120-6openalex-snapshot
Investigation of 3D pharmacophore of N-benzyl benzamide molecules of melanogenesis inhibitors using a new descriptor Klopman index: uncertainties in model
inferred← citeshttps://doi.org/10.1007/s11030-021-10217-3openalex-snapshot
Artificial intelligence to deep learning: machine intelligence approach for drug discovery
inferred← citeshttps://doi.org/10.1007/s41870-021-00737-4openalex-snapshot
PCAC: a new method for predicting compounds with activity cliff property in QSAR approach
inferred← citeshttps://doi.org/10.1016/b978-0-323-95120-3.00001-4openalex-snapshot
Computational approaches for drug-metabolizing enzymes: Concepts and challenges
inferred← citeshttps://doi.org/10.1016/b978-0-443-13681-8.00001-1openalex-snapshot
The use of computational biology in protein engineering and drug discovery
inferred← citeshttps://doi.org/10.1016/b978-0-443-30010-3.00012-xopenalex-snapshot
Application of machine learning and artificial intelligence methods in predictions of absorption, distribution, metabolism, and excretion properties of chemicals
inferred← citeshttps://doi.org/10.1016/j.aca.2011.02.004openalex-snapshot
Prediction of P2Y12 antagonists using a novel genetic algorithm-support vector machine coupled approach
inferred← citeshttps://doi.org/10.1016/j.addr.2026.115784openalex-snapshot
The predictive edge: modeling and simulation in drug product development
inferred← citeshttps://doi.org/10.1016/j.chemolab.2014.06.011openalex-snapshot
QSAR classification model for diverse series of antimicrobial agents using classification tree configured by modified particle swarm optimization
inferred← citeshttps://doi.org/10.1016/j.chemolab.2019.103853openalex-snapshot
Molecular image-based convolutional neural network for the prediction of ADMET properties
inferred← citeshttps://doi.org/10.1016/j.compbiolchem.2016.01.005openalex-snapshot
Predicting human intestinal absorption of diverse chemicals using ensemble learning based QSAR modeling approaches
inferred← citeshttps://doi.org/10.1016/j.compbiolchem.2024.108270openalex-snapshot
Integrating (deep) machine learning and cheminformatics for predicting human intestinal absorption of small molecules
inferred← citeshttps://doi.org/10.1016/j.culher.2024.02.014openalex-snapshot
Probabilistic evaluation of cultural soil heritage hazards in China from extremely imbalanced site investigation data using SMOTE-Gaussian process classification
inferred← citeshttps://doi.org/10.1016/j.xphs.2019.07.014openalex-snapshot
Constructing an In Silico Three-Class Predictor of Human Intestinal Absorption With Caco-2 Permeability and Dried-DMSO Solubility
inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00443openalex-snapshot
Practical Applications of Deep Learning To Impute Heterogeneous Drug Discovery Data
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00110openalex-snapshot
The Relative Importance of Domain Applicability Metrics for Estimating Prediction Errors in QSAR Varies with Training Set Diversity
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00753openalex-snapshot
Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Data Sets
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00542openalex-snapshot
Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Prediction Errors for Deep Neural Networks
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00718openalex-snapshot
Systematic Modeling of log D7.4 Based on Ensemble Machine Learning, Group Contribution, and Matched Molecular Pair Analysis
inferred← citeshttps://doi.org/10.1021/acs.macromol.5c03015openalex-snapshot
MacroSimGNN: Efficient and Accurate Prediction of Macromolecule Pairwise Similarity via A Graph Neural Network
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.4c00991openalex-snapshot
Establishing a Pharmacoinformatics Repository of Approved Medicines: A Database to Support Drug Product Development
inferred← citeshttps://doi.org/10.1021/acsomega.6c01866openalex-snapshot
Evaluation of Machine Learning Models for Condition Optimization in Diverse Amide Coupling Reactions
inferred← citeshttps://doi.org/10.1021/acspolymersau.3c00029openalex-snapshot
Calculating Pairwise Similarity of Polymer Ensembles via Earth Mover’s Distance
inferred← citeshttps://doi.org/10.1021/ci200615hopenalex-snapshot
Comparison of Random Forest and Pipeline Pilot Naïve Bayes in Prospective QSAR Predictions
inferred← citeshttps://doi.org/10.1021/ci300146hopenalex-snapshot
GA(M)E-QSAR: A Novel, Fully Automatic Genetic-Algorithm-(Meta)-Ensembles Approach for Binary Classification in Ligand-Based Drug Design
inferred← citeshttps://doi.org/10.1021/mp100279dopenalex-snapshot
Combinatorial QSAR Modeling of Human Intestinal Absorption
inferred← citeshttps://doi.org/10.1021/mp300023xopenalex-snapshot
ADMET Evaluation in Drug Discovery. 12. Development of Binary Classification Models for Prediction of hERG Potassium Channel Blockage
inferred← citeshttps://doi.org/10.1021/mp3006193openalex-snapshot
Physicochemical and DMPK In Silico Models: Facilitating Their Use by Medicinal Chemists
inferred← citeshttps://doi.org/10.1039/c8ra01206gopenalex-snapshot
A novel adaptive ensemble classification framework for ADME prediction
inferred← citeshttps://doi.org/10.1039/d3dd00073gopenalex-snapshot
Chemical space analysis and property prediction for carbon capture solvent molecules
inferred← citeshttps://doi.org/10.1039/d3dd00144jopenalex-snapshot
Combined data-driven and mechanism-based approaches for human-intestinal-absorption prediction in the early drug-discovery stage
inferred← citeshttps://doi.org/10.1080/03602532.2020.1765793openalex-snapshot
Advances in the study of drug metabolism – symposium report of the 12th Meeting of the International Society for the Study of Xenobiotics (ISSX)
inferred← citeshttps://doi.org/10.1080/03602532.2021.1923728openalex-snapshot
Recent developments in predicting CYP-independent metabolism
inferred← citeshttps://doi.org/10.1080/1062936x.2012.742135openalex-snapshot
Towardsin silicoidentification of the human ether-a-go-go-related gene channel blockers: discriminative vs. generative classification models
inferred← citeshttps://doi.org/10.1080/1062936x.2016.1243576openalex-snapshot
Combined QSAR-based virtual screening and fluorescence binding assay to identify natural product mediators of Interferon Regulatory Factor 7 (IRF-7) in pulmonary infection
inferred← citeshttps://doi.org/10.1124/pr.112.007336openalex-snapshot
Computational Methods in Drug Discovery
inferred← citeshttps://doi.org/10.1134/s199075081302008xopenalex-snapshot
Computer modeling of blood brain barrier permeability for physiologically active compounds
inferred← citeshttps://doi.org/10.1146/annurev-biodatasci-122120-124216openalex-snapshot
Machine Learning in Chemoinformatics and Medicinal Chemistry
inferred← citeshttps://doi.org/10.1177/2397847320978633openalex-snapshot
Improving drug safety predictions by reducing poor analytical practices
inferred← citeshttps://doi.org/10.1186/1758-2946-6-35openalex-snapshot
Proteochemometric modeling in a Bayesian framework
inferred← citeshttps://doi.org/10.1186/s13321-021-00571-7openalex-snapshot
The effect of noise on the predictive limit of QSAR models
inferred← citeshttps://doi.org/10.1371/journal.pone.0148181openalex-snapshot
Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e-Pharmacophore Modeling and Docking
inferred← citeshttps://doi.org/10.1371/journal.pone.0208362openalex-snapshot
Optimisation of children z-score calculation based on new statistical techniques
inferred← citeshttps://doi.org/10.1515/9783110559835-003openalex-snapshot
3. In Silico methods to predict solubility
inferred← citeshttps://doi.org/10.1517/17460441.2012.668182openalex-snapshot
Decision tree models for data mining in hit discovery
inferred← citeshttps://doi.org/10.17615/w4vm-f755openalex-snapshot
The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors
inferred← citeshttps://doi.org/10.18097/pbmc20146002161openalex-snapshot
Computer modeling of blood brain barrier permeability of physiologically active compounds
inferred← citeshttps://doi.org/10.2174/0113895575400393251007093333openalex-snapshot
Research Hotspots and Trends of Artificial Intelligence in Drug Discovery: A Review and Bibliometric Analysis
inferred← citeshttps://doi.org/10.2174/1389200221999200901202945openalex-snapshot
In Silico ADMET Evaluation of Natural DPP-IV Inhibitors for Rational Drug Design against Diabetes
inferred← citeshttps://doi.org/10.2174/138955712800493807openalex-snapshot
QSAR and QM/MM Approaches Applied to Drug Metabolism Prediction
inferred← citeshttps://doi.org/10.2174/1570163817666200316104404openalex-snapshot
An Analysis of QSAR Research Based on Machine Learning Concepts
inferred← citeshttps://doi.org/10.26434/chemrxiv-2022-6gx8kopenalex-snapshot
CHEMICAL SPACE ANALYSIS AND PROPERTY PREDICTION FOR CARBON CAPTURE AMINE MOLECULES
inferred← citeshttps://doi.org/10.26434/chemrxiv-2022-6gx8k-v2openalex-snapshot
CHEMICAL SPACE ANALYSIS AND PROPERTY PREDICTION FOR CARBON CAPTURE AMINE MOLECULES
inferred← citeshttps://doi.org/10.3389/fphar.2017.00238openalex-snapshot
Mode of Action Analyses of Neferine, a Bisbenzylisoquinoline Alkaloid of Lotus (Nelumbo nucifera) against Multidrug-Resistant Tumor Cells
inferred← citeshttps://doi.org/10.3390/ijms12021259openalex-snapshot
A Classification Study of Respiratory Syncytial Virus (RSV) Inhibitors by Variable Selection with Random Forest
inferred← citeshttps://doi.org/10.3390/molecules29246061openalex-snapshot
In Silico Conotoxin Studies: Progress and Prospects
inferred← citeshttps://doi.org/10.3390/pharmaceutics15112619openalex-snapshot
The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery
inferred← citeshttps://doi.org/10.3390/pharmaceutics16080978openalex-snapshot
Advances in Modeling Approaches for Oral Drug Delivery: Artificial Intelligence, Physiologically-Based Pharmacokinetics, and First-Principles Models
inferred← citeshttps://doi.org/10.3390/pharmaceutics17081002openalex-snapshot
In Silico ADME Methods Used in the Evaluation of Natural Products
inferred← citeshttps://doi.org/10.48550/arxiv.0912.1128openalex-snapshot
How to Explain Individual Classification Decisions
inferred← citeshttps://doi.org/10.48550/arxiv.1908.03569openalex-snapshot
Concepts and Applications of Conformal Prediction in Computational Drug Discovery
inferred← citeshttps://doi.org/10.5451/unibas-005676976openalex-snapshot
"In silico" prediction of drug transport across physiological barriers
inferred← citeshttps://doi.org/10.70675/00fff70azab21z46edz8364z60031c95c00fopenalex-snapshot
Applications of proteochemometrics (PCM) : from species extrapolation to cell-line sensitivity modelling
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.