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Nikolaus Stiefl
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2020 – today
- 2024
- [j22]Maximilian Beckers
, Finton Sirockin
Balancing Molecular Size, Activity, Permeability, and Other Properties: Drug Candidates in the Context of Their Chemical Structure Optimization. J. Chem. Inf. Model. 64(16): 6636-6647 (2024) - 2023
- [j21]Gregory A. Landrum, Maximilian Beckers, Jessica Lanini, Nadine Schneider, Nikolaus Stiefl, Sereina Riniker:
SIMPD: an algorithm for generating simulated time splits for validating machine learning approaches. J. Cheminformatics 15(1): 119 (2023) - [j20]Jessica Lanini
PREFER: A New Predictive Modeling Framework for Molecular Discovery. J. Chem. Inf. Model. 63(15): 4497-4504 (2023) - 2022
- [j19]Maximilian Beckers
25 Years of Small-Molecule Optimization at Novartis: A Retrospective Analysis of Chemical Series Evolution. J. Chem. Inf. Model. 62(23): 6002-6021 (2022) - [c1]Krzysztof Maziarz, Henry Richard Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin H. S. Segler, Marc Brockschmidt:
Learning to Extend Molecular Scaffolds with Structural Motifs. ICLR 2022 - 2021
- [j18]Carmen Esposito
GHOST: Adjusting the Decision Threshold to Handle Imbalanced Data in Machine Learning. J. Chem. Inf. Model. 61(6): 2623-2640 (2021) - [i1]Krzysztof Maziarz, Henry Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marc Brockschmidt:
Learning to Extend Molecular Scaffolds with Structural Motifs. CoRR abs/2103.03864 (2021) - 2020
- [j17]Franziska Kruger
Automated Identification of Chemical Series: Classifying like a Medicinal Chemist. J. Chem. Inf. Model. 60(6): 2888-2902 (2020) - [j16]Franziska Kruger
rdScaffoldNetwork: The Scaffold Network Implementation in RDKit. J. Chem. Inf. Model. 60(7): 3331-3335 (2020) - [j15]Enrico Ferrero, Sophie Brachat
Ten simple rules to power drug discovery with data science. PLoS Comput. Biol. 16(8) (2020)
2010 – 2019
- 2019
- [j14]Mahendra Awale, Finton Sirockin
Drug Analogs from Fragment-Based Long Short-Term Memory Generative Neural Networks. J. Chem. Inf. Model. 59(4): 1347-1356 (2019) - 2018
- [j13]Jan Dreher, Josef Scheiber
xMaP - An Interpretable Alignment-Free Four-Dimensional Quantitative Structure-Activity Relationship Technique Based on Molecular Surface Properties and Conformer Ensembles. J. Chem. Inf. Model. 58(1): 165-181 (2018) - 2017
- [j12]Nadine Schneider
Chemical Topic Modeling: Exploring Molecular Data Sets Using a Common Text-Mining Approach. J. Chem. Inf. Model. 57(8): 1816-1831 (2017) - 2016
- [j11]Nadine Schneider
What's What: The (Nearly) Definitive Guide to Reaction Role Assignment. J. Chem. Inf. Model. 56(12): 2336-2346 (2016) - 2015
- [j10]Nikolaus Stiefl, Peter Gedeck
FOCUS - Development of a Global Communication and Modeling Platform for Applied and Computational Medicinal Chemists. J. Chem. Inf. Model. 55(4): 896-908 (2015) - 2014
- [j9]Paolo Tosco
Bringing the MMFF force field to the RDKit: implementation and validation. J. Cheminformatics 6(1): 37 (2014) - [j8]Paolo Tosco, Nikolaus Stiefl, Gregory A. Landrum:
The integration of Open3DTOOLS into the RDKit and KNIME. J. Cheminformatics 6(S-1): 8 (2014) - 2011
- [j7]Gregory A. Landrum
Making sure there's a "give" associated with the "take": producing and using open-source software in big pharma. J. Cheminformatics 3(S-1): 3 (2011)
2000 – 2009
- 2007
- [j6]Beining Chen, Robert F. Harrison
Evaluation of machine-learning methods for ligand-based virtual screening. J. Comput. Aided Mol. Des. 21(1-3): 53-62 (2007) - 2006
- [j5]Nikolaus Stiefl, Ian A. Watson, Knut Baumann
ErG: 2D Pharmacophore Descriptions for Scaffold Hopping. J. Chem. Inf. Model. 46(1): 208-220 (2006) - [j4]Nikolaus Stiefl, Andrea Zaliani
A Knowledge-Based Weighting Approach to Ligand-Based Virtual Screening. J. Chem. Inf. Model. 46(2): 587-596 (2006) - 2005
- [j3]Nikolaus Stiefl, Knut Baumann
Structure-Based Validation of the 3D-QSAR Technique MaP. J. Chem. Inf. Model. 45(3): 739-749 (2005) - 2004
- [j2]Knut Baumann
Validation tools for variable subset regression. J. Comput. Aided Mol. Des. 18(7): 549-562 (2004) - 2003
- [j1]Nikolaus Stiefl, Gerhard Bringmann, Christian Rummey
Evaluation of extended parameter sets for the 3D-QSAR technique MaP: Implications for interpretability and model quality exemplified by antimalarially active naphthylisoquinoline alkaloids. J. Comput. Aided Mol. Des. 17(5-6): 347-365 (2003)
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