J. Wegner

发表

Which Compound to Select in Lead Optimization? Prospectively Validated Proteochemometric Models Guide Preclinical Development

H. V. van Vlijmen, A. Bender, G. V. van Westen, 2011, PloS one.

Identifying novel adenosine receptor ligands by simultaneous proteochemometric modeling of rat and human bioactivity data.

H. V. van Vlijmen, A. Bender, G. V. van Westen, 2012, Journal of medicinal chemistry.

Exploiting the Japanese Toxicogenomics Project for Predictive Modelling of Drug Toxicity

Hinrich W. H. Göhlmann, S. Hochreiter, Djork-Arné Clevert, 2012 .

Deep Learning as an Opportunity in Virtual Screening

Andreas Mayr, Thomas Unterthiner, Jörg K. Wegner, 2015 .

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

Anne E Carpenter, Yolanda T. Chong, S. Hochreiter, 2018, Cell chemical biology.

Deep Learning for Drug Target Prediction

Thomas Unterthiner, J. Wegner, Andreas Mayr, 2015 .

Multi-Task Deep Networks for Drug Target Prediction

Thomas Unterthiner, J. Wegner, G. Klambauer, 2015 .

Aiding Drug Design with Deep Neural Networks

Thomas Unterthiner, J. Wegner, G. Klambauer, 2015 .

A genetics-led approach defines the drug target landscape of 30 immune-related traits

Hinrich W. H. Göhlmann, David R. Damerell, J. Knight, 2019, Nature Genetics.

On Failure Modes of Molecule Generators and Optimizers

S. Hochreiter, J. Wegner, G. Klambauer, 2020 .

On Failure Modes of Molecule Generators and Optimizers

S. Hochreiter, J. Wegner, G. Klambauer, 2020 .

Preparing and Filtering Compound Databases for Virtual and Experimental Screening

J. Wegner, G. Tresadern, M. Cummings, 2011 .

Data and Graph Mining in Chemical Space for ADME and Activity Data Sets

Andreas Zell, Holger Fröhlich, Jörg K. Wegner, 2006 .

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

Sepp Hochreiter, Philipp Renz, S. Hochreiter, 2021, ArXiv.

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

Marwin H. S. Segler, Sepp Hochreiter, Philipp Renz, 2021, 2104.03279.

Disubstituted Bis-THF Moieties as New P2 Ligands in Nonpeptidal HIV-1 Protease Inhibitors (II).

J. Wegner, J. Unge, B. Linclau, 2015, Journal of medicinal chemistry.

Disubstituted Bis-THF Moieties as New P2 Ligands in Nonpeptidal HIV-1 Protease Inhibitors.

J. Wegner, B. Linclau, B. Kesteleyn, 2011, ACS medicinal chemistry letters.

Tales of 1,008 small molecules: phenomic profiling through live-cell imaging in a panel of reporter cell lines

Hinrich W. H. Göhlmann, Jean-Marc Neefs, Yolanda T. Chong, 2020, Scientific Reports.

Tales of 1,008 small molecules: phenomic profiling through live-cell imaging in a panel of reporter cell lines

Yolanda T. Chong, J. Neefs, Michael J. Cox, 2020, Scientific Reports.

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

E. A. del Rio-Chanona, J. Wegner, O. Méndez-Lucio, 2021, Nature Machine Intelligence.

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

Marwin H. S. Segler, S. Hochreiter, J. Wegner, 2022, J. Chem. Inf. Model..

Design and synthesis of HIV-1 protease inhibitors for a long-acting injectable drug application.

J. Wegner, B. Samuelsson, L. Baert, 2013, Bioorganic & medicinal chemistry letters.

Mining protein dynamics from sets of crystal structures using “consensus structures”

Andreas Bender, Jörg K Wegner, Gerard J P van Westen, 2010, Protein science : a publication of the Protein Society.

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

Yves Moreau, Jörg K. Wegner, Karl Meerbergen, 2017, Pattern Recognit..

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

Andreas Zell, Holger Fröhlich, Jörg K. Wegner, 2004, J. Chem. Inf. Model..

The Blue Obelisk—Interoperability in Chemical Informatics

Egon L. Willighagen, Rajarshi Guha, Christoph Steinbeck, 2006, J. Chem. Inf. Model..

Optimal assignment kernels for attributed molecular graphs

Andreas Zell, Holger Fröhlich, Jörg K. Wegner, 2005, ICML.

Assignment kernels for chemical compounds

A. Zell, H. Frohlich, J.K. Wegner, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Large-scale comparison of machine learning methods for drug target prediction on ChEMBL

Hugo Ceulemans, Sepp Hochreiter, Günter Klambauer, 2018, Chemical science.

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

Yves Moreau, Jörg K. Wegner, Vladimir I. Chupakhin, 2017, 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP).

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

Lars Carlsson, Jörg K. Wegner, Thomas J. Ashby, 2017, Journal of Cheminformatics.

On failure modes in molecule generation and optimization.

Sepp Hochreiter, Günter Klambauer, Philipp Renz, 2019, Drug discovery today. Technologies.

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

Gerard J. P. van Westen, Andreas Bender, Jörg K. Wegner, 2013, PLoS Comput. Biol..

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

Isidro Cortes-Ciriano, Gerard J. P. van Westen, John P. Overington, 2013, Journal of Cheminformatics.

Proteochemometric modeling as a tool to design selective compounds and for extrapolating to novel targets

Gerard J. P. van Westen, Andreas Bender, Jörg K. Wegner, 2011 .

Kernel Functions for Attributed Molecular Graphs – A New Similarity‐Based Approach to ADME Prediction in Classification and Regression

Andreas Zell, Holger Fröhlich, Jörg K. Wegner, 2006 .

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

Andreas Zell, Jörg K. Wegner, A. Zell, 2003, J. Chem. Inf. Comput. Sci..

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

Gerard J. P. van Westen, Andreas Bender, Jörg K. Wegner, 2013, Journal of Cheminformatics.

The compressed feature matrix—a fast method for feature based substructure search

Andreas Zell, S F Badreddin Abolmaali, Jörg K Wegner, 2003, Journal of molecular modeling.

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

Andreas Zell, Holger Fröhlich, Jörg K. Wegner, 2004, J. Chem. Inf. Model..

Disubstituted Bis-THF Moieties as New P2 Ligands in Nonpeptidal HIV-1 Protease Inhibitors.

J. Wegner, B. Linclau, B. Kesteleyn, 2011, ACS medicinal chemistry letters.

Recent advances in chemoinformatics.

Herman van Vlijmen, Jörg K Wegner, Deepak Bandyopadhyay, 2007, Journal of chemical information and modeling.

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

Jörg K. Wegner, Wolfgang De Meuter, Roel Wuyts, 2015, 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

Highly Scalable Tensor Factorization for Prediction of Drug-Protein Interaction Type

Yves Moreau, Hugo Ceulemans, Jaak Simm, 2015, NIPS 2015.

Macau: Scalable Bayesian Multi-relational Factorization with Side Information using MCMC

Yves Moreau, Hugo Ceulemans, Jaak Simm, 2015, 1509.04610.

Towards Optimal Descriptor Subset Selection with Support Vector Machines in Classification and Regression

Andreas Zell, Holger Fröhlich, Jörg K. Wegner, 2004 .

Mining protein dynamics from sets of crystal structures using “consensus structures”

H. V. van Vlijmen, A. Bender, G. V. van Westen, 2010, Protein Science.

Cheminformatics

Egon L. Willighagen, Rajarshi Guha, John P. Overington, 2012, CACM.

Large-scale comparison of machine learning methods for drug target prediction on ChEMBL

S. Hochreiter, Thomas Unterthiner, Djork-Arné Clevert, 2018, Chemical science.

Global reactivity models are impactful in industrial synthesis applications

J. Wegner, Jonas Verhoeven, N. Dyubankova, 2023, Journal of Cheminformatics.

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

Marwin H. S. Segler, J. Wegner, G. Klambauer, 2021, 2104.03279.