Christian Tyrchan

Orcid: 0000-0002-6470-984X

According to our database1, Christian Tyrchan authored at least 23 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
Evaluation of reinforcement learning in transformer-based molecular design.
J. Cheminformatics, December, 2024

Utilizing reinforcement learning for de novo drug design.
Mach. Learn., July, 2024

2023
Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification.
J. Cheminformatics, December, 2023

2022
Impact of PROTAC Linker Plasticity on the Solution Conformations and Dissociation of the Ternary Complex.
J. Chem. Inf. Model., 2022

Virtual Screening Expands the Non-Natural Amino Acid Palette for Peptide Optimization.
J. Chem. Inf. Model., 2022

Transformer-based molecular optimization beyond matched molecular pairs.
J. Cheminformatics, 2022

Autonomous Drug Design with Multi-Armed Bandits.
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.
J. Chem. Inf. Model., 2021

Molecular optimization by capturing chemist's intuition using deep neural networks.
J. Cheminformatics, 2021

Nonadditivity in public and inhouse data: implications for drug design.
J. Cheminformatics, 2021

2020
Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks.
Nat. Mach. Intell., 2020

REINVENT 2.0: An AI Tool for De Novo Drug Design.
J. Chem. Inf. Model., 2020

SMILES-based deep generative scaffold decorator for de-novo drug design.
J. Cheminformatics, 2020

2019
Randomized SMILES strings improve the quality of molecular generative models.
J. Cheminformatics, 2019

Improving Deep Generative Models with Randomized SMILES.
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.
CoRR, 2017

2016
Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design.
J. Chem. Inf. Model., 2016

2014
Hit series selection in noisy HTS data: clustering techniques, statistical tests and data visualisations.
J. Cheminformatics, 2014

HTS explorer.
J. Cheminformatics, 2014

2012
Exploiting Structural Information in Patent Specifications for Key Compound Prediction.
J. Chem. Inf. Model., 2012

How often do follow-on activities occur - trends seen in a patent database for GPCRs.
J. Cheminformatics, 2012

2010
Comparing manual and automated extraction of chemical entities from documents.
J. Cheminformatics, 2010

2009
Comparison of Molecular Fingerprint Methods on the Basis of Biological Profile Data.
J. Chem. Inf. Model., 2009


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