Igor V. Tetko

Orcid: 0000-0002-6855-0012

According to our database1, Igor V. Tetko authored at least 86 papers between 1994 and 2024.

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Bibliography

2024
Using test-time augmentation to investigate explainable AI: inconsistencies between method, model and human intuition.
J. Cheminformatics, December, 2024

When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges.
J. Chem. Inf. Model., January, 2024

Be aware of overfitting by hyperparameter optimization!
CoRR, 2024

Registries in Machine Learning-Based Drug Discovery: A Shortcut to Code Reuse.
Proceedings of the AI in Drug Discovery - First International Workshop, 2024

2023
Models Matter: The Impact of Single-Step Retrosynthesis on Synthesis Planning.
CoRR, 2023

2022
What Features of Ligands Are Relevant to the Opening of Cryptic Pockets in Drug Targets?
Informatics, 2022

Mind the Retrosynthesis Gap: Bridging the divide between Single-step and Multi-step Retrosynthesis Prediction.
CoRR, 2022

2020
Joint Virtual Special Issue on Computational Toxicology.
J. Chem. Inf. Model., 2020

From Big Data to Artificial Intelligence: chemoinformatics meets new challenges.
J. Cheminformatics, 2020

QSAR-derived affinity fingerprints (part 1): fingerprint construction and modeling performance for similarity searching, bioactivity classification and scaffold hopping.
J. Cheminformatics, 2020

Transformer-CNN: Swiss knife for QSAR modeling and interpretation.
J. Cheminformatics, 2020

GEN: highly efficient SMILES explorer using autodidactic generative examination networks.
J. Cheminformatics, 2020

Focused Library Generator: case of Mdmx inhibitors.
J. Comput. Aided Mol. Des., 2020

Beyond Chemical 1D knowledge using Transformers.
CoRR, 2020

Augmented Transformer Achieves 97% and 85% for Top5 Prediction of Direct and Classical Retro-Synthesis.
CoRR, 2020

2019
Comparative Study of Multitask Toxicity Modeling on a Broad Chemical Space.
J. Chem. Inf. Model., 2019

Transformer-CNN: Fast and Reliable tool for QSAR.
CoRR, 2019

Multitask Learning On Graph Neural Networks Applied To Molecular Property Predictions.
CoRR, 2019

Augmentation Is What You Need!
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

A Transformer Model for Retrosynthesis.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

Analysis and Modelling of False Positives in GPCR Assays.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

2018
Luciferase Advisor: High-Accuracy Model To Flag False Positive Hits in Luciferase HTS Assays.
J. Chem. Inf. Model., 2018

Synergy Effect between Convolutional Neural Networks and the Multiplicity of SMILES for Improvement of Molecular Prediction.
CoRR, 2018

2016
The development of models to predict melting and pyrolysis point data associated with several hundred thousand compounds mined from PATENTS.
J. Cheminformatics, 2016

2014
How Accurately Can We Predict the Melting Points of Drug-like Compounds?
J. Chem. Inf. Model., 2014

Prediction-driven matched molecular pairs to interpret QSARs and aid the molecular optimization process.
J. Cheminformatics, 2014

2013
Development of Dimethyl Sulfoxide Solubility Models Using 163 000 Molecules: Using a Domain Applicability Metric to Select More Reliable Predictions.
J. Chem. Inf. Model., 2013

Modeling of non-additive mixture properties using the Online CHEmical database and Modeling environment (OCHEM).
J. Cheminformatics, 2013

Chemogenomic approach to increase accuracy of QSAR modeling of inhibition activity against five major P450 isoforms.
J. Cheminformatics, 2013

Building QSAR for HTS in vitro assays - a study for the prediction of Aryl hydrocarbon receptor activators.
J. Cheminformatics, 2013

2012
ToxAlerts: A Web Server of Structural Alerts for Toxic Chemicals and Compounds with Potential Adverse Reactions.
J. Chem. Inf. Model., 2012

PLS-Optimal: A Stepwise D-Optimal Design Based on Latent Variables.
J. Chem. Inf. Model., 2012

In silico pK<sub>a</sub> prediction.
J. Cheminformatics, 2012

QSAR modeling for In vitro assays: linking ToxCast™ database to the integrated modeling framework "OCHEM".
J. Cheminformatics, 2012

The perspectives of computational chemistry modeling.
J. Comput. Aided Mol. Des., 2012

2011
A comparison of different QSAR approaches to modeling CYP450 1A2 inhibition.
J. Chem. Inf. Model., 2011

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information.
J. Cheminformatics, 2011

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information.
J. Comput. Aided Mol. Des., 2011

2010
Applicability Domains for Classification Problems: Benchmarking of Distance to Models for Ames Mutagenicity Set.
J. Chem. Inf. Model., 2010

Applicability domain for classification problems.
J. Cheminformatics, 2010

Classification of CYP450 1A2 inhibitors using PubChem data.
J. Cheminformatics, 2010

OCHEM - on-line CHEmical database & modeling environment.
J. Cheminformatics, 2010

2009
Inductive Transfer of Knowledge: Application of Multi-Task Learning and Feature Net Approaches to Model Tissue-Air Partition Coefficients.
J. Chem. Inf. Model., 2009

Associative Neural Network.
Proceedings of the Artificial Neural Networks, 2009

2008
Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis.
J. Chem. Inf. Model., 2008

Critical Assessment of QSAR Models of Environmental Toxicity against <i>Tetrahymena pyriformis: </i> Focusing on Applicability Domain and Overfitting by Variable Selection.
J. Chem. Inf. Model., 2008

FunCat functional inference with belief propagation and feature integration.
Comput. Biol. Chem., 2008

Beyond the "best" match: machine learning annotation of protein sequences by integration of different sources of information.
Bioinform., 2008

2007
Exhaustive QSPR Studies of a Large Diverse Set of Ionic Liquids: How Accurately Can We Predict Melting Points?
J. Chem. Inf. Model., 2007

2006
Correction: Spatiotemporal Expression Control Correlates with Intragenic Scaffold Matrix Attachment Regions (S/MARs) in <i>Arabidopsis thaliana</i>.
PLoS Comput. Biol., 2006

Spatiotemporal Expression Control Correlates with Intragenic Scaffold Matrix Attachment Regions (S/MARs) in <i>Arabidopsis thaliana</i>.
PLoS Comput. Biol., 2006

The Mouse Functional Genome Database (MfunGD): functional annotation of proteins in the light of their cellular context.
Nucleic Acids Res., 2006

Benchmarking of Linear and Nonlinear Approaches for Quantitative Structure-Property Relationship Studies of Metal Complexation with Ionophores.
J. Chem. Inf. Model., 2006

2005
Éclair - a web service for unravelling species origin of sequences sampled from mixed host interfaces.
Nucleic Acids Res., 2005

Virtual Computational Chemistry Laboratory - Design and Description.
J. Comput. Aided Mol. Des., 2005

Surrogate data - a secure way to share corporate data.
J. Comput. Aided Mol. Des., 2005

Gene selection from microarray data for cancer classification - a machine learning approach.
Comput. Biol. Chem., 2005

Exploiting scale-free information from expression data for cancer classification.
Comput. Biol. Chem., 2005

Super paramagnetic clustering of protein sequences.
BMC Bioinform., 2005

MIPS bacterial genomes functional annotation benchmark dataset.
Bioinform., 2005

Support vector machines for separation of mixed plant?Cpathogen EST collections based on codon usage.
Bioinform., 2005

2004
A web portal for classification of expression data using maximal margin linear programming.
Bioinform., 2004

Optimization models for cancer classification: extracting gene interaction information from microarray expression data.
Bioinform., 2004

2003
Exploiting gene interaction information from microarray expression data for cancer classification.
Proceedings of the German Conference on Bioinformatics, 2003

2002
Associative Neural Network.
Neural Process. Lett., 2002

Application of Associative Neural Networks for Prediction of Lipophilicity in ALOGPS 2.1 Program.
J. Chem. Inf. Comput. Sci., 2002

Neural Network Studies, 4. Introduction to Associative Neural Networks.
J. Chem. Inf. Comput. Sci., 2002

2001
Prediction of n-Octanol/Water Partition Coefficients from PHYSPROP Database Using Artificial Neural Networks and E-State Indices.
J. Chem. Inf. Comput. Sci., 2001

Estimation of Aqueous Solubility of Chemical Compounds Using E-State Indices.
J. Chem. Inf. Comput. Sci., 2001

Internet Software for the Calculation of the Lipophilicity and Aqueous Solubility of Chemical Compounds.
J. Chem. Inf. Comput. Sci., 2001

Computer assisted neurophysiological analysis of cell assemblies activity.
Neurocomputing, 2001

Pattern grouping algorithm and de-convolution filtering of non-stationary correlated Poisson processes.
Neurocomputing, 2001

2000
Neural Network Modeling for Estimation of Partition Coefficient Based on Atom-Type Electrotopological State Indices.
J. Chem. Inf. Comput. Sci., 2000

1998
Application of a Pruning Algorithm To Optimize Artificial Neural Networks for Pharmaceutical Fingerprinting.
J. Chem. Inf. Comput. Sci., 1998

Neural Network Studies. 3. Variable Selection in the Cascade-Correlation Learning Architecture.
J. Chem. Inf. Comput. Sci., 1998

Computer assisted neurophysiology by a distributed JAVA program.
Proceedings of the Computers and Networks in the Age of Globalization, 1998

1997
An Efficient Partition of Training Data Set Improves Speed and Accuracy of Cascade-correlation Algorithm.
Neural Process. Lett., 1997

An Enhancement of Generalization Ability in Cascade Correlation Algorithm by Avoidance of Overfitting/Overtraining Problem.
Neural Process. Lett., 1997

Efficient Partition of Learning Data Sets for Neural Network Training.
Neural Networks, 1997

Data modelling with neural networks: Advantages and limitations.
J. Comput. Aided Mol. Des., 1997

Fast combinatorial methods to estimate the probability of complex temporal patterns of spikes.
Biol. Cybern., 1997

A Comparative Study of Pattern Detection Algorithm and Dynamical System Approach Using Simulated Spike Trains.
Proceedings of the Artificial Neural Networks, 1997

1996
Neural Network Studies, 2. Variable Selection.
J. Chem. Inf. Comput. Sci., 1996

1995
Neural network studies, 1. Comparison of overfitting and overtraining.
J. Chem. Inf. Comput. Sci., 1995

1994
Input Parameters' estimation via neural networks.
Proceedings of the 2nd European Symposium on Artificial Neural Networks, 1994

Evaluation of potential HIV-1 reverse transcriptase inhibitors by artificial neural networks.
Proceedings of the Seventh Annual IEEE Symposium on Computer-Based Medical Systems (CBMS'94), 1994


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