Stephan A. Sieber

According to our database, Stephan A. Sieber authored at least 7 papers between 2022 and 2024.

Collaborative distances:

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

2024

Effectiveness of molecular fingerprints for exploring the chemical space of natural products.

Davide Boldini, Davide Ballabio, Viviana Consonni, Roberto Todeschini, Francesca Grisoni, Stephan A. Sieber

J. Cheminformatics, December, 2024

Synergizing Chemical Structures and Bioassay Descriptions for Enhanced Molecular Property Prediction in Drug Discovery.

Maximilian G. Schuh, Davide Boldini, Stephan A. Sieber

J. Chem. Inf. Model., 2024

Machine Learning-Driven Data Valuation for Optimizing High-Throughput Screening Pipelines.

Joshua Hesse, Davide Boldini, Stephan A. Sieber

J. Chem. Inf. Model., 2024

Barlow Twins Deep Neural Network for Advanced 1D Drug-Target Interaction Prediction.

Maximilian G. Schuh, Davide Boldini, Stephan A. Sieber

CoRR, 2024

TwinBooster: Synergising Large Language Models with Barlow Twins and Gradient Boosting for Enhanced Molecular Property Prediction.

Maximilian G. Schuh, Davide Boldini, Stephan A. Sieber

CoRR, 2024

2023

Practical guidelines for the use of gradient boosting for molecular property prediction.

Davide Boldini, Francesca Grisoni, Daniel Kuhn, Lukas Friedrich, Stephan A. Sieber

J. Cheminformatics, December, 2023

2022

Tuning gradient boosting for imbalanced bioassay modelling with custom loss functions.

Davide Boldini, Lukas Friedrich, Daniel Kuhn, Stephan A. Sieber

J. Cheminformatics, 2022