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Johannes Kirchmair
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2020 – today
- 2024
- [j35]Ya Chen
, Thomas Seidel
Active Learning Approach for Guiding Site-of-Metabolism Measurement and Annotation. J. Chem. Inf. Model. 64(2): 348-358 (2024) - [j34]Hosein Fooladi, Steffen Hirte, Johannes Kirchmair
Quantifying the Hardness of Bioactivity Prediction Tasks for Transfer Learning. J. Chem. Inf. Model. 64(10): 4031-4046 (2024) - [j33]Matthias Welsch
Deciphering Molecular Embeddings with Centered Kernel Alignment. J. Chem. Inf. Model. 64(19): 7303-7312 (2024) - 2023
- [j32]Magdalena Wiercioch, Johannes Kirchmair
DNN-PP: A novel Deep Neural Network approach and its applicability in drug-related property prediction. Expert Syst. Appl. 213(Part C): 119055 (2023) - [j31]Karla Gonzalez-Ponce
School of cheminformatics in Latin America. J. Cheminformatics 15(1): 82 (2023) - 2021
- [j30]Fidele Ntie-Kang
Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop. J. Cheminformatics 13(1): 64 (2021) - [j29]Marina Garcia de Lomana
ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted Bioactivities. J. Chem. Inf. Model. 61(7): 3255-3272 (2021) - [i1]José L. Medina-Franco
Rationality over fashion and hype in drug design. F1000Research 10: 397 (2021) - 2020
- [j28]Neann Mathai
Validation strategies for target prediction methods. Briefings Bioinform. 21(3): 791-802 (2020) - [j27]Conrad Stork
NERDD: a web portal providing access to in silico tools for drug discovery. Bioinform. 36(4): 1291-1292 (2020) - [j26]Ya Chen
Scope of 3D Shape-Based Approaches in Predicting the Macromolecular Targets of Structurally Complex Small Molecules Including Natural Products and Macrocyclic Ligands. J. Chem. Inf. Model. 60(6): 2858-2875 (2020)
2010 – 2019
- 2019
- [j25]Nils-Ole Friedrich
Conformator: A Novel Method for the Generation of Conformer Ensembles. J. Chem. Inf. Model. 59(2): 731-742 (2019) - [j24]Conrad Stork
Hit Dexter 2.0: Machine-Learning Models for the Prediction of Frequent Hitters. J. Chem. Inf. Model. 59(3): 1030-1043 (2019) - [j23]Martin Sícho
FAME 3: Predicting the Sites of Metabolism in Synthetic Compounds and Natural Products for Phase 1 and Phase 2 Metabolic Enzymes. J. Chem. Inf. Model. 59(8): 3400-3412 (2019) - 2018
- [j22]Ya Chen
Characterization of the Chemical Space of Known and Readily Obtainable Natural Products. J. Chem. Inf. Model. 58(8): 1518-1532 (2018) - 2017
- [j21]Nils-Ole Friedrich, Agnes Meyder
High-Quality Dataset of Protein-Bound Ligand Conformations and Its Application to Benchmarking Conformer Ensemble Generators. J. Chem. Inf. Model. 57(3): 529-539 (2017) - [j20]Christina de Bruyn Kops
Alignment-Based Prediction of Sites of Metabolism. J. Chem. Inf. Model. 57(6): 1258-1264 (2017) - [j19]Martin Sícho
FAME 2: Simple and Effective Machine Learning Model of Cytochrome P450 Regioselectivity. J. Chem. Inf. Model. 57(8): 1832-1846 (2017) - [j18]Ya Chen
Data Resources for the Computer-Guided Discovery of Bioactive Natural Products. J. Chem. Inf. Model. 57(9): 2099-2111 (2017) - [j17]Nils-Ole Friedrich
Benchmarking Commercial Conformer Ensemble Generators. J. Chem. Inf. Model. 57(11): 2719-2728 (2017) - 2014
- [j16]Jonathan D. Tyzack
Cytochrome P450 site of metabolism prediction from 2D topological fingerprints using GPU accelerated probabilistic classifiers. J. Cheminformatics 6(1): 29 (2014) - 2013
- [j15]Johannes Kirchmair, Andrew Howlett, Julio E. Peironcely, Daniel S. Murrell, Mark J. Williamson, Samuel E. Adams, Thomas Hankemeier, Leo van Buren, Guus Duchateau, Werner Klaffke, Robert C. Glen:
Quantifying the shifts in physicochemical property space introduced by the metabolism of small organic molecules. J. Cheminformatics 5(S-1): 12 (2013) - [j14]Johannes Kirchmair
How Do Metabolites Differ from Their Parent Molecules and How Are They Excreted? J. Chem. Inf. Model. 53(2): 354-367 (2013) - [j13]Johannes Kirchmair
FAst MEtabolizer (FAME): A Rapid and Accurate Predictor of Sites of Metabolism in Multiple Species by Endogenous Enzymes. J. Chem. Inf. Model. 53(11): 2896-2907 (2013) - 2012
- [j12]Johannes Kirchmair
Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms. J. Chem. Inf. Model. 52(3): 617-648 (2012) - 2010
- [j11]Gudrun M. Spitzer, Mathias Heiss, Martina Mangold, Patrick Markt, Johannes Kirchmair
One Concept, Three Implementations of 3D Pharmacophore-Based Virtual Screening: Distinct Coverage of Chemical Search Space. J. Chem. Inf. Model. 50(7): 1241-1247 (2010)
2000 – 2009
- 2009
- [j10]Johannes Kirchmair
How To Optimize Shape-Based Virtual Screening: Choosing the Right Query and Including Chemical Information. J. Chem. Inf. Model. 49(3): 678-692 (2009) - [j9]Gudrun M. Spitzer, Bernd Wellenzohn, Patrick Markt, Johannes Kirchmair
Hydrogen-Bonding Patterns of Minor Groove-Binder-DNA Complexes Reveal Criteria for Discovery of New Scaffolds. J. Chem. Inf. Model. 49(4): 1063-1069 (2009) - [j8]Pekka Tiikkainen, Patrick Markt, Gerhard Wolber
Critical Comparison of Virtual Screening Methods against the MUV Data Set. J. Chem. Inf. Model. 49(10): 2168-2178 (2009) - 2008
- [j7]Johannes Kirchmair
Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection - What can we learn from earlier mistakes? J. Comput. Aided Mol. Des. 22(3-4): 213-228 (2008) - [j6]Patrick Markt, Caroline McGoohan, Brian Walker, Johannes Kirchmair
Discovery of Novel Cathepsin S Inhibitors by Pharmacophore-Based Virtual High-Throughput Screening. J. Chem. Inf. Model. 48(8): 1693-1705 (2008) - 2007
- [j5]Patrick Markt, Daniela Schuster
Pharmacophore modeling and parallel screening for PPAR ligands. J. Comput. Aided Mol. Des. 21(10-11): 575-590 (2007) - [j4]Jiabo Li, Tedman Ehlers, Jon M. Sutter, Shikha Varma-O'Brien, Johannes Kirchmair
CAESAR: A New Conformer Generation Algorithm Based on Recursive Buildup and Local Rotational Symmetry Consideration. J. Chem. Inf. Model. 47(5): 1923-1932 (2007) - [j3]Johannes Kirchmair
Fast and Efficient in Silico 3D Screening: Toward Maximum Computational Efficiency of Pharmacophore-Based and Shape-Based Approaches. J. Chem. Inf. Model. 47(6): 2182-2196 (2007) - 2006
- [j2]Johannes Kirchmair
Comparative Performance Assessment of the Conformational Model Generators Omega and Catalyst: A Large-Scale Survey on the Retrieval of Protein-Bound Ligand Conformations. J. Chem. Inf. Model. 46(4): 1848-1861 (2006) - 2005
- [j1]Johannes Kirchmair
Comparative Analysis of Protein-Bound Ligand Conformations with Respect to Catalyst's Conformational Space Subsampling Algorithms. J. Chem. Inf. Model. 45(2): 422-430 (2005)
Coauthor Index
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