On the public citation graph
Bias-Correction of Regression Models: A Case Study on hERG Inhibition
0 signed · 78 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.
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known work and none has been retracted — and get a dated CiteStamped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.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(sici)1521-3773(19991004)38:19<2894::aid-anie2894>3.0.co;2-fopenalex-snapshot
“Scaffold-Hopping” by Topological Pharmacophore Search: A Contribution to Virtual Screening
inferredcites →https://doi.org/10.1002/cmdc.200700041openalex-snapshot
Predicting Lipophilicity of Drug‐Discovery Molecules using Gaussian Process Models
inferredcites →https://doi.org/10.1002/cmdc.200700221openalex-snapshot
A Composite Model for hERG Blockade
inferredcites →https://doi.org/10.1002/med.20019openalex-snapshot
QT prolongation through hERG K+ channel blockade: Current knowledge and strategies for the early prediction during drug development
inferredcites →https://doi.org/10.1007/978-0-387-21606-5openalex-snapshot
The Elements of Statistical Learning
inferredcites →https://doi.org/10.1007/978-1-60327-101-1_10openalex-snapshot
Associative Neural Network
inferredcites →https://doi.org/10.1007/s10822-007-9125-zopenalex-snapshot
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules
inferredcites →https://doi.org/10.1007/s10822-007-9160-9openalex-snapshot
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules
inferredcites →https://doi.org/10.1016/j.bmc.2007.12.042openalex-snapshot
Design and synthesis of trans 2-(furan-2-yl)vinyl heteroaromatic iodides with antitumour activity
inferredcites →https://doi.org/10.1016/j.bmcl.2006.12.061openalex-snapshot
A quantitative assessment of hERG liability as a function of lipophilicity
inferredcites →https://doi.org/10.1016/j.neucom.2005.05.015openalex-snapshot
From outliers to prototypes: Ordering data
inferredcites →https://doi.org/10.1016/j.vascn.2004.06.003openalex-snapshot
Variability in the measurement of hERG potassium channel inhibition: Effects of temperature and stimulus pattern
inferredcites →https://doi.org/10.1016/j.vascn.2006.02.003openalex-snapshot
Optimisation and validation of a medium-throughput electrophysiology-based hERG assay using IonWorks™ HT
inferredcites →https://doi.org/10.1016/s0928-0987(00)00162-7openalex-snapshot
VolSurf: a new tool for the pharmacokinetic optimization of lead compounds
inferredcites →https://doi.org/10.1016/s1359-6446(04)03278-7openalex-snapshot
Predictive in silico modeling for hERG channel blockers
inferredcites →https://doi.org/10.1021/ci010379oopenalex-snapshot
Neural Network Studies. 4. Introduction to Associative Neural Networks
inferredcites →https://doi.org/10.1021/ci034006uopenalex-snapshot
Prediction of Aqueous Solubility and Partition Coefficient Optimized by a Genetic Algorithm Based Descriptor Selection Method
inferredcites →https://doi.org/10.1021/ci049737oopenalex-snapshot
Classifying ‘Drug-likeness' with Kernel-Based Learning Methods
inferredcites →https://doi.org/10.1021/ci0503762openalex-snapshot
Model Selection Based on Structural Similarity−Method Description and Application to Water Solubility Prediction
inferredcites →https://doi.org/10.1021/ci0504014openalex-snapshot
logD7.4 Modeling Using Bayesian Regularized Neural Networks. Assessment and Correction of the Errors of Prediction
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/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/ci700197xopenalex-snapshot
QSAR Modeling Using Automatically Updating Correction Libraries: Application to a Human Plasma Protein Binding Model
inferredcites →https://doi.org/10.1021/ci800304topenalex-snapshot
Similarity-Based Classifier Using Topomers to Provide a Knowledge Base for hERG Channel Inhibition
inferredcites →https://doi.org/10.1021/jm049254bopenalex-snapshot
Greater Than the Sum of Its Parts: Combining Models for Useful ADMET Prediction
inferredcites →https://doi.org/10.1021/jm060379lopenalex-snapshot
Medicinal Chemistry of hERG Optimizations: Highlights and Hang-Ups
inferredcites →https://doi.org/10.1021/jm701122qopenalex-snapshot
Generation of a Set of Simple, Interpretable ADMET Rules of Thumb
inferredcites →https://doi.org/10.1021/mp0700413openalex-snapshot
Machine Learning Models for Lipophilicity and Their Domain of Applicability
inferredcites →https://doi.org/10.1021/mp700124eopenalex-snapshot
hERG Classification Model Based on a Combination of Support Vector Machine Method and GRIND Descriptors
inferredcites →https://doi.org/10.1023/b:stco.0000035301.49549.88openalex-snapshot
A tutorial on support vector regression
inferredcites →https://doi.org/10.1038/nature04710openalex-snapshot
hERG potassium channels and cardiac arrhythmia
inferredcites →https://doi.org/10.1038/nrd1108openalex-snapshot
The impact of drug-induced QT interval prolongation on drug discovery and development
inferredcites →https://doi.org/10.1046/j.1540-8167.2004.03534.xopenalex-snapshot
Drug‐Induced Torsades de Pointes and Implications for Drug Development
inferredcites →https://doi.org/10.1080/00401706.1999.10485951openalex-snapshot
Statistical Learning Theory
inferredcites →https://doi.org/10.1089/adt.2005.3.47openalex-snapshot
Characterization of a hERG Screen Using the IonWorks HT: Comparison to a hERG Rubidium Efflux Screen
inferredcites →https://doi.org/10.1093/oso/9780198538493.001.0001openalex-snapshot
Neural Networks for Pattern Recognition
inferredcites →https://doi.org/10.1109/72.914517openalex-snapshot
An introduction to kernel-based learning algorithms
inferredcites →https://doi.org/10.1109/iconip.2002openalex-snapshot
Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02.
inferredcites →https://doi.org/10.1109/mcas.2006.1688199openalex-snapshot
Ensemble based systems in decision making
inferredcites →https://doi.org/10.1111/j.1747-0285.2008.00747.xopenalex-snapshot
Combining Cluster Analysis, Feature Selection and Multiple Support Vector Machine Models for the Identification of Human Ether‐a‐go‐go Related Gene Channel Blocking Compounds
inferredcites →https://doi.org/10.1145/1015330.1015418openalex-snapshot
Predictive automatic relevance determination by expectation propagation
inferredcites →https://doi.org/10.1517/17425255.2.1.81openalex-snapshot
Molecular mechanisms for drug interactions with hERG that cause long QT syndrome
inferredcites →https://doi.org/10.2170/physiolsci.rv011408openalex-snapshot
In Silico Prediction of the Chemical Block of Human Ether-a-Go-Go-Related Gene (hERG) K+ Current
inferredcites →https://doi.org/10.2174/092986707782794087openalex-snapshot
Predictive Models for hERG Channel Blockers: Ligand-Based and Structure-Based Approaches
inferredcites →https://doi.org/10.2174/092986709787002736openalex-snapshot
In Silico Prediction of Drug Properties
inferredcites →https://doi.org/10.2174/156802606778108915openalex-snapshot
Machine Learning Techniques for In Silico Modeling of Drug Metabolism
inferredcites →https://doi.org/10.2174/157340908784533256openalex-snapshot
Predictive QSAR Models for Polyspecific Drug Targets: The Importance of Feature Selection
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/9781119282594.ch3openalex-snapshot
Computational Approaches for Predicting hERG Activity
inferred← citeshttps://doi.org/10.1002/9783527645121.ch1openalex-snapshot
Current Modeling Methods Used in QSAR/QSPR
inferred← citeshttps://doi.org/10.1002/9783527677016.ch1openalex-snapshot
De NovoDesign: From Models to Molecules
inferred← citeshttps://doi.org/10.1002/cem.1302openalex-snapshot
Impact of standardization sample design on Tikhonov regularization variants for spectroscopic calibration maintenance and transfer
inferred← citeshttps://doi.org/10.1002/cmdc.200900469openalex-snapshot
From Machine Learning to Natural Product Derivatives that Selectively Activate Transcription Factor PPARγ
inferred← citeshttps://doi.org/10.1002/minf.200900009openalex-snapshot
Target Profile Prediction: Cross‐Activation of Peroxisome Proliferator‐Activated Receptor (PPAR) and Farnesoid X Receptor (FXR)
inferred← citeshttps://doi.org/10.1007/s00894-011-1136-yopenalex-snapshot
Predicting the potency of hERG K+ channel inhibition by combining 3D-QSAR pharmacophore and 2D-QSAR models
inferred← citeshttps://doi.org/10.1016/j.addr.2015.03.003openalex-snapshot
Computational investigations of hERG channel blockers: New insights and current predictive models
inferred← citeshttps://doi.org/10.1016/j.bmcl.2011.07.006openalex-snapshot
Novel and highly potent histamine H3 receptor ligands. Part 1: withdrawing of hERG activity
inferred← citeshttps://doi.org/10.1016/j.bmcl.2014.11.063openalex-snapshot
Rodent selectivity of piperidine-4-yl-1H-indoles, a series of CC chemokine receptor-3 (CCR3) antagonists: Insights from a receptor model
inferred← citeshttps://doi.org/10.1016/j.chemolab.2012.06.006openalex-snapshot
A consensus modeling approach to update a spectroscopic calibration
inferred← citeshttps://doi.org/10.1016/j.comtox.2017.05.001openalex-snapshot
Performance of machine learning algorithms for qualitative and quantitative prediction drug blockade of hERG1 channel
inferred← citeshttps://doi.org/10.1016/j.jelectrocard.2021.10.005openalex-snapshot
Electrocardiogram-based index for the assessment of drug-induced hERG potassium channel block
inferred← citeshttps://doi.org/10.1016/j.vascn.2013.12.003openalex-snapshot
Progress in computational toxicology
inferred← citeshttps://doi.org/10.1016/s1877-1173(10)91006-5openalex-snapshot
The T1R2/T1R3 Sweet Receptor and TRPM5 Ion Channel
inferred← citeshttps://doi.org/10.1021/acs.jcim.6c03072openalex-snapshot
25 Years of Cardiac Ion Channel QSAR: From hERG Dominance to Multi-Channel Modeling
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00150openalex-snapshot
The Catch-22 of Predicting hERG Blockade Using Publicly Accessible Bioactivity Data
inferred← citeshttps://doi.org/10.1021/ct400195dopenalex-snapshot
Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies
inferred← citeshttps://doi.org/10.1021/jm500317aopenalex-snapshot
Matched Molecular Pair Analysis: Significance and the Impact of Experimental Uncertainty
inferred← citeshttps://doi.org/10.1080/17460441.2021.1931114openalex-snapshot
Modeling approaches for reducing safety-related attrition in drug discovery and development: a review on myelotoxicity, immunotoxicity, cardiovascular toxicity, and liver toxicity
inferred← citeshttps://doi.org/10.1109/icisa.2010.5480392openalex-snapshot
Determination of Water Content in Automobile Lubricant Using Near-Infrared Spectroscopy Improved by Machine Learning Analysis
inferred← citeshttps://doi.org/10.14279/depositonce-3309openalex-snapshot
Novel Machine Learning Methods for Computational Chemistry
inferred← citeshttps://doi.org/10.1517/17425255.2010.489550openalex-snapshot
Machine learning algorithms for the prediction of hERG and CYP450 binding in drug development
inferred← citeshttps://doi.org/10.2174/138945013804806460openalex-snapshot
Human Ether-a-Go-Go-Related Gene Channel Blockers and its Structural Analysis for Drug Design
inferred← citeshttps://doi.org/10.2174/15680266113139990036openalex-snapshot
Recent Developments in Computational Prediction of hERG Blockage
inferred← citeshttps://doi.org/10.2174/1568026614666140506124442openalex-snapshot
Tuning hERG Out: Antitarget QSAR Models for Drug Development
inferred← citeshttps://doi.org/10.4155/fmc.15.18openalex-snapshot
In Silico Prediction of hERG Inhibition
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.