Jörg K. Wegner

According to our database, Jörg K. Wegner authored at least 30 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Pretraining Graph Transformers with Atom-in-a-Molecule Quantum Properties for Improved ADMET Modeling.

Alessio Fallani, Ramil I. Nugmanov, Jose A. Arjona-Medina, Jörg Kurt Wegner, Alexandre Tkatchenko, Kostiantyn Chernichenko

CoRR, 2024

Gradient Guided Hypotheses: A unified solution to enable machine learning models on scarce and noisy data regimes.

Paulo Neves, Jörg K. Wegner, Philippe Schwaller

CoRR, 2024

ReacLLaMA: Merging chemical and textual information in chemical reactivity AI models.

Aline Hartgers, Ramil I. Nugmanov, Kostiantyn Chernichenko, Jörg Kurt Wegner

CoRR, 2024

Atom-Level Quantum Pretraining Enhances the Spectral Perception of Molecular Graphs in Graphormer.

Alessio Fallani, José Antonio Arjona-Medina, Konstantin Chernichenko, Ramil I. Nugmanov, Jörg Kurt Wegner, Alexandre Tkatchenko

Proceedings of the AI in Drug Discovery - First International Workshop, 2024

2023

Correction: Global reactivity models are impactful in industrial synthesis applications.

Paulo Neves, Kelly McClure, Jonas Verhoeven, Natalia Dyubankova, Ramil I. Nugmanov, Andrey Gedich, Sairam Menon, Zhicai Shi, Jörg K. Wegner

J. Cheminformatics, December, 2023

Global reactivity models are impactful in industrial synthesis applications.

Paulo Neves, Kelly McClure, Jonas Verhoeven, Natalia Dyubankova, Ramil I. Nugmanov, Andrey Gedich, Sairam Menon, Zhicai Shi, Jörg K. Wegner

J. Cheminformatics, December, 2023

2022

Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks.

Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Marwin H. S. Segler, Sepp Hochreiter, Günter Klambauer

J. Chem. Inf. Model., 2022

Bidirectional Graphormer for Reactivity Understanding: Neural Network Trained to Reaction Atom-to-Atom Mapping Task.

Ramil I. Nugmanov, Natalia Dyubankova, Andrey Gedich, Jörg Kurt Wegner

J. Chem. Inf. Model., 2022

2021

A geometric deep learning approach to predict binding conformations of bioactive molecules.

Oscar Méndez-Lucio, Mazen Ahmad, Ehecatl Antonio del Rio-Chanona, Jörg Kurt Wegner

Nat. Mach. Intell., 2021

Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction.

Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Sepp Hochreiter, Günter Klambauer

CoRR, 2021

2020

Industry-scale application and evaluation of deep learning for drug target prediction.

Noé Sturm, Andreas Mayr, Thanh Le Van, Vladimir I. Chupakhin, Hugo Ceulemans, Jörg K. Wegner, José Felipe Golib Dzib, Nina Jeliazkova, Yves Vandriessche, Stanislav Böhm, Vojtech Cima, Jan Martinovic, Nigel Greene, Tom Vander Aa, Thomas J. Ashby, Sepp Hochreiter, Ola Engkvist, Günter Klambauer, Hongming Chen

J. Cheminformatics, 2020

2019

Fast semi-supervised discriminant analysis for binary classification of large data sets.

Joris Tavernier, Jaak Simm, Karl Meerbergen, Jörg Kurt Wegner, Hugo Ceulemans, Yves Moreau

Pattern Recognit., 2019

ExCAPE-DB: An Integrated Large Scale Dataset Facilitating Big Data Analysis in Chemogenomics.

Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

SMURFF: A High-Performance Framework for Matrix Factorization Methods.

Tom Vander Aa, Imen Chakroun, Tom Ashby, Jaak Simm, Adam Arany, Yves Moreau, Thanh Le Van, José Felipe Golib Dzib, Jörg K. Wegner, Vladimir I. Chupakhin, Hugo Ceulemans, Roel Wuyts, Wilfried Verachtert

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2017

Erratum to: ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics.

Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Ola Engkvist, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen

J. Cheminformatics, 2017

ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics.

Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Ola Engkvist, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen

J. Cheminformatics, 2017

Scaling machine learning for target prediction in drug discovery using Apache Spark.

Dries Harnie, Mathijs Saey, Alexander E. Vapirev, Jörg Kurt Wegner, Andrey Gedich, Marvin N. Steijaert, Hugo Ceulemans, Roel Wuyts, Wolfgang De Meuter

Future Gener. Comput. Syst., 2017

Macau: Scalable Bayesian factorization with high-dimensional side information using MCMC.

Jaak Simm, Adam Arany, Pooya Zakeri, Tom Haber, Jörg K. Wegner, Vladimir I. Chupakhin, Hugo Ceulemans, Yves Moreau

Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

2015

Scaling Machine Learning for Target Prediction in Drug Discovery using Apache Spark.

Dries Harnie, Alexander E. Vapirev, Jörg Kurt Wegner, Andrey Gedich, Marvin N. Steijaert, Roel Wuyts, Wolfgang De Meuter

Proceedings of the 15th IEEE/ACM International Symposium on Cluster, 2015

2013

Significantly Improved HIV Inhibitor Efficacy Prediction Employing Proteochemometric Models Generated From Antivirogram Data.

Gerard J. P. van Westen, Alwin Hendriks, Jörg K. Wegner, Adriaan P. IJzerman, Herman W. T. van Vlijmen, Andreas Bender

PLoS Comput. Biol., 2013

Benchmarking of protein descriptor sets in proteochemometric modeling (part 1): comparative study of 13 amino acid descriptor sets.

Gerard J. P. van Westen, Remco F. Swier, Jörg K. Wegner, Adriaan P. IJzerman, Herman W. T. van Vlijmen, Andreas Bender

J. Cheminformatics, 2013

Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets.

Gerard J. P. van Westen, Remco F. Swier, Isidro Cortes-Ciriano, Jörg K. Wegner, John P. Overington, Adriaan P. IJzerman, Herman W. T. van Vlijmen, Andreas Bender

J. Cheminformatics, 2013

2012

Cheminformatics.

Jörg K. Wegner, Aaron D. Sterling, Rajarshi Guha, Andreas Bender, Jean-Loup Faulon, Janna Hastings, Noel M. O'Boyle, John P. Overington, Herman van Vlijmen, Egon L. Willighagen

Commun. ACM, 2012

2010

Molecular bioactivity extrapolation to novel targets by support vector machines.

Gerard J. P. van Westen, Jörg K. Wegner, Adriaan P. IJzerman, Herman W. T. van Vlijmen, Andreas Bender

J. Cheminformatics, 2010

2007

Molecular Query Language (MQL)A Context-Free Grammar for Substructure Matching.

Ewgenij Proschak, Jörg K. Wegner, Andreas Schüller, Gisbert Schneider, Uli Fechner

J. Chem. Inf. Model., 2007

2006

The Blue Obelisk-Interoperability in Chemical Informatics.

Rajarshi Guha, Michael T. Howard, Geoffrey R. Hutchison, Peter Murray-Rust, Henry S. Rzepa, Christoph Steinbeck, Jörg K. Wegner, Egon L. Willighagen

J. Chem. Inf. Model., 2006

2005

Optimal assignment kernels for attributed molecular graphs.

Holger Fröhlich, Jörg K. Wegner, Florian Sieker, Andreas Zell

Proceedings of the Machine Learning, 2005

2004

Feature Selection for Descriptor Based Classification Models. 2. Human Intestinal Absorption (HIA).

Jörg K. Wegner, Holger Fröhlich, Andreas Zell

J. Chem. Inf. Model., 2004

Feature Selection for Descriptor Based Classification Models. 1. Theory and GA-SEC Algorithm.

Jörg K. Wegner, Holger Fröhlich, Andreas Zell

J. Chem. Inf. Model., 2004

2003

Prediction of Aqueous Solubility and Partition Coefficient Optimized by a Genetic Algorithm Based Descriptor Selection Method.

Jörg K. Wegner, Andreas Zell

J. Chem. Inf. Comput. Sci., 2003