D. Reker

发表

Revealing the Macromolecular Targets of Fragment-Like Natural Products.

G. Schneider, P. Schneider, Tiago Rodrigues, 2015, Angewandte Chemie.

Active learning for computational chemogenomics.

G. Schneider, P. Schneider, D. Reker, 2017, Future medicinal chemistry.

Counting on Natural Products for Drug Design

G. Schneider, P. Schneider, Tiago Rodrigues, 2016 .

Revealing the macromolecular targets of complex natural products.

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

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

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

Vaccination with anti-idiotype antibody ganglidiomab mediates a GD2-specific anti-neuroblastoma immune response

D. Reker, C. Helm, D. Seidel, 2013, Cancer Immunology, Immunotherapy.

“Inactive” ingredients in oral medications

D. Reker, G. Traverso, K. Anger, 2019, Science Translational Medicine.

Counting on natural products for drug design.

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

Computational advances in combating colloidal aggregation in drug discovery

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

Deorphaning pyrrolopyrazines as potent multi-target antimalarial agents.

Christian P. Koch, G. Schneider, F. Diederich, 2014, Angewandte Chemie.

Computationally guided high-throughput design of self-assembling drug nanoparticles

Ameya R. Kirtane, R. Langer, D. Reker, 2019, bioRxiv.

Machine Learning Uncovers Food- and Excipient-Drug Interactions

Ameya R. Kirtane, R. Langer, D. Reker, 2020, Cell reports.

New use of an old drug: inhibition of breast cancer stem cells by benztropine mesylate

G. Schneider, D. Reker, M. Detmar, 2016, Oncotarget.

Deorphaning the Macromolecular Targets of the Natural Anticancer Compound Doliculide.

G. Schneider, P. Schneider, D. Reker, 2016, Angewandte Chemie.

Diagnosing capillary leak in critically ill patients: development of an innovative scoring instrument for non-invasive detection

D. Reker, H. Buerkle, S. Heinrich, 2021, Annals of Intensive Care.

Dynamic Monitoring of Systemic Biomarkers with Gastric Sensors

D. Reker, G. Traverso, R. Baron, 2021, Advanced science.

A machine learning liver-on-a-chip system for safer drug formulation

W. Goessling, D. Reker, G. Traverso, 2022, bioRxiv.

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

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

De novo design and optimization of Aurora A kinase inhibitors

Gisbert Schneider, Daniel Reker, Michael Detmar, 2013 .

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.

Artificial intelligence in chemistry and drug design

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

Validated detection of anti-GD2 antibody ch14.18/CHO in serum of neuroblastoma patients using anti-idiotype antibody ganglidiomab.

D. Reker, D. Seidel, H. Lode, 2013, Journal of immunological methods.

Common non-epigenetic drugs as epigenetic modulators.

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

Fragment-Based De Novo Design Reveals a Small-Molecule Inhibitor of Helicobacter Pylori HtrA.

G. Schneider, S. Wessler, Tiago Rodrigues, 2015, Angewandte Chemie.

Selection of Informative Examples in Chemogenomic Datasets.

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

Combating small molecule aggregation with machine learning

D. Reker, Yen-Chu Lin, T. Rodrigues, 2021, Cell Reports Physical Science.

Cheminformatic Analysis of Natural Product Fragments.

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

Bioinformatic challenges in targeted proteomics.

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

Oral mRNA delivery using capsule-mediated gastrointestinal tissue injections

Ameya R. Kirtane, D. Reker, R. Langer, 2022, Matter.

Practical considerations for active machine learning in drug discovery.

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

Multi-objective active machine learning rapidly improves structure–activity models and reveals new protein–protein interaction inhibitors† †Electronic supplementary information (ESI) available: Details about computational comparisons and all screening results. See DOI: 10.1039/c5sc04272k

P Schneider, D Reker, G Schneider, 2016, Chemical science.

Adaptive Optimization of Chemical Reactions with Minimal Experimental Information

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

Robotically handled whole-tissue culture system for the screening of oral drug formulations

R. Langer, D. Reker, G. Traverso, 2020, Nature Biomedical Engineering.

Active-learning strategies in computer-assisted drug discovery.

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

Evolving and Nano Data Enabled Machine Intelligence for Chemical Reaction Optimization

D. Reker, T. Rodrigues, G. Bernardes, 2018 .

Matrix‐based Molecular Descriptors for Prospective Virtual Compound Screening

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

Robotically handled whole-tissue culture system for the screening of oral drug formulations

R. Langer, D. Reker, G. Traverso, 2020, Nature Biomedical Engineering.

Spotting and designing promiscuous ligands for drug discovery.

P Schneider, M Röthlisberger, D Reker, 2016, Chemical communications.

De Novo Fragment Design for Drug Discovery and Chemical Biology.

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

Small Random Forest Models for Effective Chemogenomic Active Learning

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

Improving molecular machine learning through adaptive subsampling with active learning

D. Reker, Yan Xiang, Yujing Wen, 2023, Digital Discovery.

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

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

Counting on natural products for drug design.

G. Schneider, P. Schneider, Tiago Rodrigues, 2016, Nature chemistry.

Interpretable Molecular Property Predictions Using Marginalized Graph Kernels

D. Reker, Yu-Hang Tang, Guang Lin, 2023, J. Chem. Inf. Model..

Deorphaning the Macromolecular Targets of the Natural Anticancer Compound Doliculide.

G. Schneider, P. Schneider, D. Reker, 2016, Angewandte Chemie.

Chemography of Natural Product Space

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

Coping with polypharmacology by computational medicinal chemistry.

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

Angiopoietin-2 is associated with capillary leak and predicts complications after cardiac surgery

D. Reker, G. Trummer, J. Muehlschlegel, 2023, Annals of Intensive Care.