Computation of mutual information from Hidden Markov Models. - Daniel Reker; Stefan Katzenbeisser 001; Kay Hamacher (Comput. Biol. Chem., 2010)

Target prediction by cascaded self-organizing maps for ligand de-orphaning and side-effect investigation. - Daniel Reker; Tiago Rodrigues; Petra Schneider; Gisbert Schneider (J. Cheminformatics, 2014)

Advanced Editorial to announce a JCAMD Special Issue on Artificial Intelligence and Machine Learning. - Daniel Reker; Richard A. Lewis (J. Comput. Aided Mol. Des., 2019)

Artificial intelligence in chemistry and drug design. - Nathan Brown; Peter Ertl; Richard A. Lewis; Torsten Luksch; Daniel Reker; Nadine Schneider (J. Comput. Aided Mol. Des., 2020)

Combating small molecule aggregation with machine learning. - Kuan Lee; Ann Yang; Yen-Chu Lin; Daniel Reker; Gonçalo J. L. Bernardes; Tiago Rodrigues (CoRR, 2021)

Interpretable Molecular Property Predictions Using Marginalized Graph Kernels. - Yan Xiang; Yu-Hang Tang; Guang Lin 001; Daniel Reker (J. Chem. Inf. Model., 2023)

DeepDelta: predicting ADMET improvements of molecular derivatives with deep learning. - Zachary Fralish; Ashley Chen; Paul Skaluba; Daniel Reker (J. Cheminformatics, 2023)

Characterizing emerging companies in computational drug development. - Chloe Markey; Samuel Croset; Olivia Ruth Woolley; Can Martin Buldun; Christian Koch; Daniel Koller; Daniel Reker (Nat. Comput. Sci., 2024)

Data-driven learning of structure augments quantitative prediction of biological responses. - Yuanchi Ha; Helena R. Ma; Feilun Wu; Andrea Weiss; Katherine Duncker; Helen Z. Xu; Jia Lu; Max Golovsky; Daniel Reker; Lingchong You (PLoS Comput. Biol., 2024)

Taking a deep dive with active learning for drug discovery. - Zachary Fralish; Daniel Reker (Nat. Comput. Sci., 2024)