Kogej T - Search Results

1

On the use of real-world datasets for reaction yield prediction.

Saebi M, Nan B, Herr JE, Wahlers J, Guo Z, Zurański AM, Kogej T, Norrby PO, Doyle AG, Chawla NV, Wiest O. Saebi M, et al. Among authors: kogej t. Chem Sci. 2023 Mar 13;14(19):4997-5005. doi: 10.1039/d2sc06041h. eCollection 2023 May 17. Chem Sci. 2023. PMID: 37206399 Free PMC article.

2

Datasets and their influence on the development of computer assisted synthesis planning tools in the pharmaceutical domain.

Thakkar A, Kogej T, Reymond JL, Engkvist O, Bjerrum EJ. Thakkar A, et al. Among authors: kogej t. Chem Sci. 2019 Nov 5;11(1):154-168. doi: 10.1039/c9sc04944d. eCollection 2020 Jan 7. Chem Sci. 2019. PMID: 32110367 Free PMC article.

3

Automated stopped-flow library synthesis for rapid optimisation and machine learning directed experimentation.

Avila C, Cassani C, Kogej T, Mazuela J, Sarda S, Clayton AD, Kossenjans M, Green CP, Bourne RA. Avila C, et al. Among authors: kogej t. Chem Sci. 2022 Sep 13;13(41):12087-12099. doi: 10.1039/d2sc03016k. eCollection 2022 Oct 26. Chem Sci. 2022. PMID: 36349112 Free PMC article.

4

LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design.

Fialková V, Zhao J, Papadopoulos K, Engkvist O, Bjerrum EJ, Kogej T, Patronov A. Fialková V, et al. Among authors: kogej t. J Chem Inf Model. 2022 May 9;62(9):2046-2063. doi: 10.1021/acs.jcim.1c00469. Epub 2021 Aug 30. J Chem Inf Model. 2022. PMID: 34460269 Review.

5

Prediction of the Chemical Context for Buchwald-Hartwig Coupling Reactions.

Genheden S, Mårdh A, Lahti G, Engkvist O, Olsson S, Kogej T. Genheden S, et al. Among authors: kogej t. Mol Inform. 2022 Aug;41(8):e2100294. doi: 10.1002/minf.202100294. Epub 2022 Feb 22. Mol Inform. 2022. PMID: 35122702 Free PMC article.

6

AI-assisted synthesis prediction.

Johansson S, Thakkar A, Kogej T, Bjerrum E, Genheden S, Bastys T, Kannas C, Schliep A, Chen H, Engkvist O. Johansson S, et al. Among authors: kogej t. Drug Discov Today Technol. 2019 Dec;32-33:65-72. doi: 10.1016/j.ddtec.2020.06.002. Epub 2020 Jul 11. Drug Discov Today Technol. 2019. PMID: 33386096 Review.

7

Automated recycling of chemistry for virtual screening and library design.

Vainio MJ, Kogej T, Raubacher F. Vainio MJ, et al. Among authors: kogej t. J Chem Inf Model. 2012 Jul 23;52(7):1777-86. doi: 10.1021/ci300157m. Epub 2012 Jul 2. J Chem Inf Model. 2012. PMID: 22657574

8

Accurate Hit Estimation for Iterative Screening Using Venn-ABERS Predictors.

Buendia R, Kogej T, Engkvist O, Carlsson L, Linusson H, Johansson U, Toccaceli P, Ahlberg E. Buendia R, et al. Among authors: kogej t. J Chem Inf Model. 2019 Mar 25;59(3):1230-1237. doi: 10.1021/acs.jcim.8b00724. Epub 2019 Feb 22. J Chem Inf Model. 2019. PMID: 30726080

9

Exploring in silico prediction of the unbound brain-to-plasma drug concentration ratio: model validation, renewal, and interpretation.

Varadharajan S, Winiwarter S, Carlsson L, Engkvist O, Anantha A, Kogej T, Fridén M, Stålring J, Chen H. Varadharajan S, et al. Among authors: kogej t. J Pharm Sci. 2015 Mar;104(3):1197-206. doi: 10.1002/jps.24301. Epub 2014 Dec 24. J Pharm Sci. 2015. PMID: 25546343

10

Investigating Pharmacological Similarity by Charting Chemical Space.

Buonfiglio R, Engkvist O, Várkonyi P, Henz A, Vikeved E, Backlund A, Kogej T. Buonfiglio R, et al. Among authors: kogej t. J Chem Inf Model. 2015 Nov 23;55(11):2375-90. doi: 10.1021/acs.jcim.5b00375. Epub 2015 Nov 2. J Chem Inf Model. 2015. PMID: 26484706

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