Daniel Reker

发表

Target prediction by cascaded self-organizing maps for ligand de-orphaning and side-effect investigation

Petra Schneider, Gisbert Schneider, Daniel Reker, 2014, Journal of Cheminformatics.

Chemography of Natural Product Space

Petra Schneider, Gisbert Schneider, Kimito Funatsu, 2015, Planta Medica.

Adaptive Optimization of Chemical Reactions with Minimal Experimental Information

Daniel Reker, Tiago Rodrigues, Emily A. Hoyt, 2020, Cell Reports Physical Science.

Geospatial Web Mining for Emergency Management

Heiko Paulheim, Florian Probst, Christian Fritz, 2010 .

Chemically Advanced Template Search (CATS) for Scaffold-Hopping and Prospective Target Prediction for ‘Orphan’ Molecules

Petra Schneider, Gisbert Schneider, Daniel Reker, 2013, Molecular informatics.

Active-learning strategies in computer-assisted drug discovery.

Gisbert Schneider, Daniel Reker, G. Schneider, 2015, Drug discovery today.

Advanced Editorial to announce a JCAMD Special Issue on Artificial Intelligence and Machine Learning

Daniel Reker, Richard A. Lewis, 2019, Journal of Computer-Aided Molecular Design.

Artificial intelligence in chemistry and drug design

Peter Ertl, Nathan Brown, Daniel Reker, 2020, Journal of Computer-Aided Molecular Design.

Selection of Informative Examples in Chemogenomic Datasets.

Daniel Reker, J B Brown, D. Reker, 2018, Methods in molecular biology.

Computation of mutual information from Hidden Markov Models

Stefan Katzenbeisser, Kay Hamacher, Daniel Reker, 2010, Comput. Biol. Chem..

Identifying the macromolecular targets of de novo-designed chemical entities through self-organizing map consensus

Petra Schneider, Gisbert Schneider, Daniel Reker, 2014, Proceedings of the National Academy of Sciences.

Predicting protein-ligand interactions based on bow-pharmacological space and Bayesian additive regression trees

Li Li, Hao Dai, Haishuai Wang, 2019, Scientific Reports.

Cheminformatic Analysis of Natural Product Fragments.

Daniel Reker, D. Reker, 2019, Progress in the chemistry of organic natural products.

De Novo Fragment Design for Drug Discovery and Chemical Biology.

Petra Schneider, Gisbert Schneider, Daniel Reker, 2015, Angewandte Chemie.

Bioinformatic challenges in targeted proteomics.

Lars Malmström, Daniel Reker, D. Reker, 2012, Journal of proteome research.

Small Random Forest Models for Effective Chemogenomic Active Learning

Daniel Reker, J. B. Brown, Christin Rakers, 2017 .

Practical considerations for active machine learning in drug discovery.

Daniel Reker, D. Reker, 2019, Drug discovery today. Technologies.

Combating small molecule aggregation with machine learning pdf

Daniel Reker, Kuan Lee, Ann Yang, 2021, Cell Reports Physical Science.

De novo design and optimization of Aurora A kinase inhibitors

Gisbert Schneider, Daniel Reker, Michael Detmar, 2013 .

Computational advances in combating colloidal aggregation in drug discovery

Daniel Reker, Gonçalo J. L. Bernardes, Tiago Rodrigues, 2019, Nature Chemistry.

Matrix‐based Molecular Descriptors for Prospective Virtual Compound Screening

Roberto Todeschini, Petra Schneider, Gisbert Schneider, 2017, Molecular informatics.

Coping with polypharmacology by computational medicinal chemistry.

Petra Schneider, Gisbert Schneider, Daniel Reker, 2014, Chimia.

Common non-epigenetic drugs as epigenetic modulators.

Jörn Lötsch, Petra Schneider, Gisbert Schneider, 2013, Trends in molecular medicine.

Counting on natural products for drug design.

Petra Schneider, Gisbert Schneider, Daniel Reker, 2016, Nature chemistry.

Multidimensional de novo design reveals 5-HT2B receptor-selective ligands.

Gisbert Schneider, Daniel Reker, Guido Koch, 2015, Angewandte Chemie.

Revealing the macromolecular targets of complex natural products.

Petra Schneider, Gisbert Schneider, Daniel Reker, 2014, Nature chemistry.