Christian Tyrchan

According to our database, Christian Tyrchan authored at least 24 papers between 2009 and 2024.

Collaborative distances:

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

2024

Evaluation of reinforcement learning in transformer-based molecular design.

Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist

J. Cheminformatics, December, 2024

Utilizing reinforcement learning for de novo drug design.

Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani

Mach. Learn., July, 2024

Diversity-Aware Reinforcement Learning for de novo Drug Design.

Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani

CoRR, 2024

2023

Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification.

Yumeng Zhang, Janosch Menke, Jiazhen He, Eva Nittinger, Christian Tyrchan, Oliver Koch, Hongtao Zhao

J. Cheminformatics, December, 2023

2022

Impact of PROTAC Linker Plasticity on the Solution Conformations and Dissociation of the Ternary Complex.

Dhanushka Weerakoon, Rodrigo J. Carbajo, Leonardo De Maria, Christian Tyrchan, Hongtao Zhao

J. Chem. Inf. Model., 2022

Virtual Screening Expands the Non-Natural Amino Acid Palette for Peptide Optimization.

Kosala Amarasinghe, Leonardo De Maria, Christian Tyrchan, Leif A. Eriksson, Jens Sadowski, Dusan Petrovic

J. Chem. Inf. Model., 2022

Transformer-based molecular optimization beyond matched molecular pairs.

Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, Ola Engkvist

J. Cheminformatics, 2022

Autonomous Drug Design with Multi-Armed Bandits.

Hampus Gummesson Svensson, Esben Jannik Bjerrum, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Unraveling the Allosteric Cross-Talk between the Coactivator Peptide and the Ligand-Binding Site in the Glucocorticoid Receptor.

Giuseppina La Sala, Anders Gunnarsson, Karl Edman, Christian Tyrchan, Anders Hogner, Andrey I. Frolov

J. Chem. Inf. Model., 2021

Molecular optimization by capturing chemist's intuition using deep neural networks.

Jiazhen He, Huifang You, Emil Sandström, Eva Nittinger, Esben Jannik Bjerrum, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist

J. Cheminformatics, 2021

Nonadditivity in public and inhouse data: implications for drug design.

Dea Gogishvili, Eva Nittinger, Christian Margreitter, Christian Tyrchan

J. Cheminformatics, 2021

2020

Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks.

Panagiotis-Christos Kotsias, Josep Arús-Pous, Hongming Chen, Ola Engkvist, Christian Tyrchan, Esben Jannik Bjerrum

Nat. Mach. Intell., 2020

REINVENT 2.0: An AI Tool for De Novo Drug Design.

Thomas Blaschke, Josep Arús-Pous, Hongming Chen, Christian Margreitter, Christian Tyrchan, Ola Engkvist, Kostas Papadopoulos, Atanas Patronov

J. Chem. Inf. Model., 2020

SMILES-based deep generative scaffold decorator for de-novo drug design.

Josep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist

J. Cheminformatics, 2020

2019

Randomized SMILES strings improve the quality of molecular generative models.

Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist

J. Cheminformatics, 2019

Improving Deep Generative Models with Randomized SMILES.

Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist

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

2017

Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks.

Marwin H. S. Segler, Thierry Kogej, Christian Tyrchan, Mark P. Waller

CoRR, 2017

2016

Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design.

Christoph Grebner, Jessica Iegre, Johan Ulander, Karl Edman, Anders Hogner, Christian Tyrchan

J. Chem. Inf. Model., 2016

2014

Hit series selection in noisy HTS data: clustering techniques, statistical tests and data visualisations.

Christoph Müller, Daniel L. Ormsby, Isabella Feierberg, Ola Engkvist, Christian Tyrchan, Michael J. Hartshorn

J. Cheminformatics, 2014

HTS explorer.

Christoph Müller, Isabella Feierberg, Ola Engkvist, Christian Tyrchan

J. Cheminformatics, 2014

2012

Exploiting Structural Information in Patent Specifications for Key Compound Prediction.

Christian Tyrchan, Jonas Boström, Fabrizio Giordanetto, Jon Winter, Sorel Muresan

J. Chem. Inf. Model., 2012

How often do follow-on activities occur - trends seen in a patent database for GPCRs.

Christian Tyrchan, Sorel Muresan

J. Cheminformatics, 2012

2010

Comparing manual and automated extraction of chemical entities from documents.

Christian Tyrchan, Sorel Muresan

J. Cheminformatics, 2010

2009

Comparison of Molecular Fingerprint Methods on the Basis of Biological Profile Data.

Andreas Steffen, Thierry Kogej, Christian Tyrchan, Ola Engkvist

J. Chem. Inf. Model., 2009