Ola Engkvist

Morteza Haghir Chehreghani

Alexander Schliep

Proceedings of the IEEE International Conference on Big Data, 2023

Industry-Scale Orchestrated Federated Learning for Drug Discovery.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Icolos: a workflow manager for structure-based post-processing of de novo generated small molecules.

[BibT_eX]

[DOI]

Bioinform., October, 2022

Author Correction: Improving de novo molecular design with curriculum learning.

[BibT_eX]

[DOI]

Jeff Guo

Vendy Fialková

Juan Diego Arango

Nat. Mach. Intell., 2022

Improving de novo molecular design with curriculum learning.

[BibT_eX]

[DOI]

Jeff Guo

Vendy Fialková

Juan Diego Arango

Nat. Mach. Intell., 2022

Fast prediction of distances between synthetic routes with deep learning.

[BibT_eX]

[DOI]

Samuel Genheden

Mach. Learn. Sci. Technol., 2022

Exploring Graph Traversal Algorithms in Graph-Based Molecular Generation.

[BibT_eX]

[DOI]

Rocío Mercado

Hampus Gummesson Svensson

J. Chem. Inf. Model., 2022

LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2022

De Novo Drug Design Using Reinforcement Learning with Graph-Based Deep Generative Models.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2022

Human-in-the-loop assisted de novo molecular design.

[BibT_eX]

[DOI]

J. Cheminformatics, 2022

Transformer-based molecular optimization beyond matched molecular pairs.

[BibT_eX]

[DOI]

J. Cheminformatics, 2022

Industry-Scale Orchestrated Federated Learning for Drug Discovery.

[BibT_eX]

[DOI]

CoRR, 2022

Implications of topological imbalance for representation learning on biomedical knowledge graphs.

[BibT_eX]

[DOI]

Briefings Bioinform., 2022

A review of biomedical datasets relating to drug discovery: a knowledge graph perspective.

[BibT_eX]

[DOI]

Briefings Bioinform., 2022

Autonomous Drug Design with Multi-Armed Bandits.

[BibT_eX]

[DOI]

Christian Tyrchan

Morteza Haghir Chehreghani

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Graph networks for molecular design.

[BibT_eX]

[DOI]

Mach. Learn. Sci. Technol., 2021

Artificial applicability labels for improving policies in retrosynthesis prediction.

[BibT_eX]

[DOI]

Amol Thakkar

Mach. Learn. Sci. Technol., 2021

Comparative Study of Deep Generative Models on Chemical Space Coverage.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2021

Comparison of Chemical Structure and Cell Morphology Information for Multitask Bioactivity Predictions.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2021

Clustering of Synthetic Routes Using Tree Edit Distance.

[BibT_eX]

[DOI]

Samuel Genheden

J. Chem. Inf. Model., 2021

Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty.

[BibT_eX]

[DOI]

J. Cheminformatics, 2021

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

[BibT_eX]

[DOI]

J. Cheminformatics, 2021

DockStream: a docking wrapper to enhance de novo molecular design.

[BibT_eX]

[DOI]

J. Cheminformatics, 2021

MAIP: a web service for predicting blood-stage malaria inhibitors.

[BibT_eX]

[DOI]

J. Cheminformatics, 2021

Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery.

[BibT_eX]

[DOI]

CoRR, 2021

A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective.

[BibT_eX]

[DOI]

CoRR, 2021

Parallel Capsule Networks for Classification of White Blood Cells.

[BibT_eX]

[DOI]

Juan P. Vigueras-Guillén

Arijit Patra

Panagiotis-Christos Kotsias

Frank Seeliger

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020

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

[BibT_eX]

[DOI]

Nat. Mach. Intell., 2020

Multisolvent Models for Solvation Free Energy Predictions Using 3D-RISM Hydration Thermodynamic Descriptors.

[BibT_eX]

[DOI]

Vigneshwari Subramanian

J. Chem. Inf. Model., 2020

Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Protein-Ligand Predictions.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2020

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

[BibT_eX]

[DOI]

Thomas Blaschke

Josep Arús-Pous

Hongming Chen

J. Chem. Inf. Model., 2020

Building attention and edge message passing neural networks for bioactivity and physical-chemical property prediction.

[BibT_eX]

[DOI]

J. Cheminformatics, 2020

From Big Data to Artificial Intelligence: chemoinformatics meets new challenges.

[BibT_eX]

[DOI]

Igor V. Tetko

Panagiotis-Christos Kotsias

J. Cheminformatics, 2020

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

[BibT_eX]

[DOI]

Noé Sturm

Andreas Mayr

Thanh Le Van

Vladimir I. Chupakhin

Hugo Ceulemans

Jörg K. Wegner

José Felipe Golib Dzib

J. Cheminformatics, 2020

AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning.

[BibT_eX]

[DOI]

J. Cheminformatics, 2020

Molecular representations in AI-driven drug discovery: a review and practical guide.

[BibT_eX]

[DOI]

J. Cheminformatics, 2020

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

[BibT_eX]

[DOI]

J. Cheminformatics, 2020

2019

Application of Bioactivity Profile-Based Fingerprints for Building Machine Learning Models.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2019

Accurate Hit Estimation for Iterative Screening Using Venn-ABERS Predictors.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2019

A de novo molecular generation method using latent vector based generative adversarial network.

[BibT_eX]

[DOI]

Oleksii Prykhodko

Simon Johansson

J. Cheminformatics, 2019

Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold hopping capability.

[BibT_eX]

[DOI]

J. Cheminformatics, 2019

Randomized SMILES strings improve the quality of molecular generative models.

[BibT_eX]

[DOI]

J. Cheminformatics, 2019

Exploring the GDB-13 chemical space using deep generative models.

[BibT_eX]

[DOI]

J. Cheminformatics, 2019

Attention and Edge Memory Convolution for Bioactivity Prediction.

[BibT_eX]

[DOI]

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

Neural Network Guided Tree-Search Policies for Synthesis Planning.

[BibT_eX]

[DOI]

Improving Deep Generative Models with Randomized SMILES.

[BibT_eX]

[DOI]

2018

Orthologue chemical space and its influence on target prediction.

[BibT_eX]

[DOI]

Bioinform., 2018

Venn-Abers predictors for improved compound iterative screening in drug discovery.

[BibT_eX]

[DOI]

Proceedings of the 7th Symposium on Conformal and Probabilistic Prediction and Applications, 2018

2017

Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published?

[BibT_eX]

[DOI]

Stephanie K. Ashenden

Thierry Kogej

Andreas Bender

J. Chem. Inf. Model., November, 2017

Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., July, 2017

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

[BibT_eX]

[DOI]

Jiangming Sun

Nina Jeliazkova

Vladimir I. Chupakhin

José Felipe Golib Dzib

J. Cheminformatics, 2017

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

[BibT_eX]

[DOI]

Jiangming Sun

Nina Jeliazkova

Vladimir I. Chupakhin

José Felipe Golib Dzib

J. Cheminformatics, 2017

Molecular de-novo design through deep reinforcement learning.

[BibT_eX]

[DOI]

J. Cheminformatics, 2017

Application of generative autoencoder in de novo molecular design.

[BibT_eX]

[DOI]

CoRR, 2017

Using Conformal Prediction to Prioritize Compound Synthesis in Drug Discovery.

[BibT_eX]

[DOI]

Proceedings of the Conformal and Probabilistic Prediction and Applications, 2017

2015

Investigating Pharmacological Similarity by Charting Chemical Space.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2015

Target prediction utilising negative bioactivity data covering large chemical space.

[BibT_eX]

[DOI]

J. Cheminformatics, 2015

2014

Ligand-Based Target Prediction with Signature Fingerprints.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2014

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

[BibT_eX]

[DOI]

J. Cheminformatics, 2014

HTS explorer.

[BibT_eX]

[DOI]

J. Cheminformatics, 2014

2010

Molecular Topology Analysis of the Differences between Drugs, Clinical Candidate Compounds, and Bioactive Molecules.

[BibT_eX]

[DOI]

Hongming Chen

Yidong Yang

J. Chem. Inf. Model., 2010

2009

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

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2009

ProSAR: A New Methodology for Combinatorial Library Design.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2009

2006

Multifingerprint Based Similarity Searches for Targeted Class Compound Selection.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2006

2003

Prediction of CNS Activity of Compound Libraries Using Substructure Analysis.

[BibT_eX]

[DOI]

Paul Wrede

Ulrich Rester

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

2002

High-Throughput, In Silico Prediction of Aqueous Solubility Based on One- and Two-Dimensional Descriptors.

[BibT_eX]

[DOI]

Jose Manuel Hermida-Ramón

Paul Wrede

J. Chem. Inf. Comput. Sci., 2002

1998

Theoretical study of intermolecular potential energy surface for HCl dimer: Example of nonspherical atom-atom exchange repulsion interaction.

[BibT_eX]

[DOI]