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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
2017 2
2018 2
2019 6
2020 3
2021 0
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12 results
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NERDD: a web portal providing access to in silico tools for drug discovery.
Stork C, Embruch G, Šícho M, de Bruyn Kops C, Chen Y, Svozil D, Kirchmair J. Stork C, et al. Bioinformatics. 2020 Feb 15;36(4):1291-1292. doi: 10.1093/bioinformatics/btz695. Bioinformatics. 2020. PMID: 32077475
Hit Dexter 2.0: Machine-Learning Models for the Prediction of Frequent Hitters.
Stork C, Chen Y, Šícho M, Kirchmair J. Stork C, et al. J Chem Inf Model. 2019 Mar 25;59(3):1030-1043. doi: 10.1021/acs.jcim.8b00677. Epub 2019 Jan 25. J Chem Inf Model. 2019. PMID: 30624935
PAIN(S) relievers for medicinal chemists: how computational methods can assist in hit evaluation.
Stork C, Kirchmair J. Stork C, et al. Future Med Chem. 2018 Jul 1;10(13):1533-1535. doi: 10.4155/fmc-2018-0116. Epub 2018 Jun 29. Future Med Chem. 2018. PMID: 29956552 No abstract available.
NP-Scout: Machine Learning Approach for the Quantification and Visualization of the Natural Product-Likeness of Small Molecules.
Chen Y, Stork C, Hirte S, Kirchmair J. Chen Y, et al. Among authors: stork c. Biomolecules. 2019 Jan 24;9(2):43. doi: 10.3390/biom9020043. Biomolecules. 2019. PMID: 30682850 Free PMC article.
Skin Doctor CP: Conformal Prediction of the Skin Sensitization Potential of Small Organic Molecules.
Wilm A, Norinder U, Agea MI, de Bruyn Kops C, Stork C, Kühnl J, Kirchmair J. Wilm A, et al. Among authors: stork c. Chem Res Toxicol. 2020 Dec 9. doi: 10.1021/acs.chemrestox.0c00253. Online ahead of print. Chem Res Toxicol. 2020. PMID: 33295759
Skin Doctor: Machine Learning Models for Skin Sensitization Prediction that Provide Estimates and Indicators of Prediction Reliability.
Wilm A, Stork C, Bauer C, Schepky A, Kühnl J, Kirchmair J. Wilm A, et al. Among authors: stork c. Int J Mol Sci. 2019 Sep 28;20(19):4833. doi: 10.3390/ijms20194833. Int J Mol Sci. 2019. PMID: 31569429 Free PMC article.
GLORY: Generator of the Structures of Likely Cytochrome P450 Metabolites Based on Predicted Sites of Metabolism.
de Bruyn Kops C, Stork C, Šícho M, Kochev N, Svozil D, Jeliazkova N, Kirchmair J. de Bruyn Kops C, et al. Among authors: stork c. Front Chem. 2019 Jun 12;7:402. doi: 10.3389/fchem.2019.00402. eCollection 2019. Front Chem. 2019. PMID: 31249827 Free PMC article.
ALADDIN: Docking Approach Augmented by Machine Learning for Protein Structure Selection Yields Superior Virtual Screening Performance.
Fan N, Bauer CA, Stork C, de Bruyn Kops C, Kirchmair J. Fan N, et al. Among authors: stork c. Mol Inform. 2020 Apr;39(4):e1900103. doi: 10.1002/minf.201900103. Epub 2019 Nov 8. Mol Inform. 2020. PMID: 31663691 Free PMC article.
FAME 3: Predicting the Sites of Metabolism in Synthetic Compounds and Natural Products for Phase 1 and Phase 2 Metabolic Enzymes.
Šícho M, Stork C, Mazzolari A, de Bruyn Kops C, Pedretti A, Testa B, Vistoli G, Svozil D, Kirchmair J. Šícho M, et al. Among authors: stork c. J Chem Inf Model. 2019 Aug 26;59(8):3400-3412. doi: 10.1021/acs.jcim.9b00376. Epub 2019 Aug 13. J Chem Inf Model. 2019. PMID: 31361490
Hit Dexter: A Machine-Learning Model for the Prediction of Frequent Hitters.
Stork C, Wagner J, Friedrich NO, de Bruyn Kops C, Šícho M, Kirchmair J. Stork C, et al. ChemMedChem. 2018 Mar 20;13(6):564-571. doi: 10.1002/cmdc.201700673. Epub 2018 Feb 1. ChemMedChem. 2018. PMID: 29285887
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