Cadet F - Search Results

1

Metabolic Fluxes Using Deep Learning Based on Enzyme Variations: Application to Glycolysis in Entamoeba histolytica.

Oulia F, Charton P, Lo-Thong-Viramoutou O, Acevedo-Rocha CG, Liu W, Huynh D, Damour C, Wang J, Cadet F. Oulia F, et al. Among authors: cadet f. Int J Mol Sci. 2024 Dec 13;25(24):13390. doi: 10.3390/ijms252413390. Int J Mol Sci. 2024. PMID: 39769154 Free PMC article.

2

Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches.

Lo-Thong O, Charton P, Cadet XF, Grondin-Perez B, Saavedra E, Damour C, Cadet F. Lo-Thong O, et al. Among authors: cadet xf, cadet f. Sci Rep. 2020 Aug 10;10(1):13446. doi: 10.1038/s41598-020-70295-5. Sci Rep. 2020. PMID: 32778715 Free PMC article.

3

Flux prediction using artificial neural network (ANN) for the upper part of glycolysis.

Ajjolli Nagaraja A, Fontaine N, Delsaut M, Charton P, Damour C, Offmann B, Grondin-Perez B, Cadet F. Ajjolli Nagaraja A, et al. Among authors: cadet f. PLoS One. 2019 May 8;14(5):e0216178. doi: 10.1371/journal.pone.0216178. eCollection 2019. PLoS One. 2019. PMID: 31067238 Free PMC article.

4

Learning Strategies in Protein Directed Evolution.

Cadet XF, Gelly JC, van Noord A, Cadet F, Acevedo-Rocha CG. Cadet XF, et al. Among authors: cadet f. Methods Mol Biol. 2022;2461:225-275. doi: 10.1007/978-1-0716-2152-3_15. Methods Mol Biol. 2022. PMID: 35727454 Review.

5

Non-linearity of Metabolic Pathways Critically Influences the Choice of Machine Learning Model.

Lo-Thong-Viramoutou O, Charton P, Cadet XF, Grondin-Perez B, Saavedra E, Damour C, Cadet F. Lo-Thong-Viramoutou O, et al. Among authors: cadet xf, cadet f. Front Artif Intell. 2022 Jun 10;5:744755. doi: 10.3389/frai.2022.744755. eCollection 2022. Front Artif Intell. 2022. PMID: 35757298 Free PMC article.

6

Application of fourier transform and proteochemometrics principles to protein engineering.

Cadet F, Fontaine N, Vetrivel I, Ng Fuk Chong M, Savriama O, Cadet X, Charton P. Cadet F, et al. Among authors: cadet x. BMC Bioinformatics. 2018 Oct 16;19(1):382. doi: 10.1186/s12859-018-2407-8. BMC Bioinformatics. 2018. PMID: 30326841 Free PMC article.

7

Insights into Comparative Modeling of V_HH Domains.

Vattekatte AM, Cadet F, Gelly JC, de Brevern AG. Vattekatte AM, et al. Among authors: cadet f. Int J Mol Sci. 2021 Sep 9;22(18):9771. doi: 10.3390/ijms22189771. Int J Mol Sci. 2021. PMID: 34575931 Free PMC article.

8

V_HH Structural Modelling Approaches: A Critical Review.

Vishwakarma P, Vattekatte AM, Shinada N, Diharce J, Martins C, Cadet F, Gardebien F, Etchebest C, Nadaradjane AA, de Brevern AG. Vishwakarma P, et al. Among authors: cadet f. Int J Mol Sci. 2022 Mar 28;23(7):3721. doi: 10.3390/ijms23073721. Int J Mol Sci. 2022. PMID: 35409081 Free PMC article. Review.

9

General Trends of the Camelidae Antibody V_HHs Domain Dynamics.

Vattekatte AM, Diharce J, Rebehmed J, Cadet F, Gardebien F, Etchebest C, de Brevern AG. Vattekatte AM, et al. Among authors: cadet f. Int J Mol Sci. 2023 Feb 24;24(5):4511. doi: 10.3390/ijms24054511. Int J Mol Sci. 2023. PMID: 36901942 Free PMC article.

10

A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes.

Cadet F, Fontaine N, Li G, Sanchis J, Ng Fuk Chong M, Pandjaitan R, Vetrivel I, Offmann B, Reetz MT. Cadet F, et al. Sci Rep. 2018 Nov 13;8(1):16757. doi: 10.1038/s41598-018-35033-y. Sci Rep. 2018. PMID: 30425279 Free PMC article.

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