Chambost J - Search Results

1

Machine learning for prediction of euploidy in human embryos: in search of the best-performing model and predictive features.

De Gheselle S, Jacques C, Chambost J, Blank C, Declerck K, De Croo I, Hickman C, Tilleman K. De Gheselle S, et al. Among authors: chambost j. Fertil Steril. 2022 Apr;117(4):738-746. doi: 10.1016/j.fertnstert.2021.11.029. Epub 2022 Jan 19. Fertil Steril. 2022. PMID: 35058042 Free article.

2

Data sharing: using blockchain and decentralized data technologies to unlock the potential of artificial intelligence: What can assisted reproduction learn from other areas of medicine?

Hickman CFL, Alshubbar H, Chambost J, Jacques C, Pena CA, Drakeley A, Freour T. Hickman CFL, et al. Among authors: chambost j. Fertil Steril. 2020 Nov;114(5):927-933. doi: 10.1016/j.fertnstert.2020.09.160. Fertil Steril. 2020. PMID: 33160515 Free article.

3

Predictive modeling in reproductive medicine: Where will the future of artificial intelligence research take us?

Curchoe CL, Malmsten J, Bormann C, Shafiee H, Flores-Saiffe Farias A, Mendizabal G, Chavez-Badiola A, Sigaras A, Alshubbar H, Chambost J, Jacques C, Pena CA, Drakeley A, Freour T, Hajirasouliha I, Hickman CFL, Elemento O, Zaninovic N, Rosenwaks Z. Curchoe CL, et al. Among authors: chambost j. Fertil Steril. 2020 Nov;114(5):934-940. doi: 10.1016/j.fertnstert.2020.10.040. Fertil Steril. 2020. PMID: 33160516 Free article. Review.

4

Predicting the number of oocytes retrieved from controlled ovarian hyperstimulation with machine learning.

Ferrand T, Boulant J, He C, Chambost J, Jacques C, Pena CA, Hickman C, Reignier A, Fréour T. Ferrand T, et al. Among authors: chambost j. Hum Reprod. 2023 Oct 3;38(10):1918-1926. doi: 10.1093/humrep/dead163. Hum Reprod. 2023. PMID: 37581894 Free PMC article.

5

Seeking arrangements: cell contact as a cleavage-stage biomarker.

He C, Karpavičiūtė N, Hariharan R, Lees L, Jacques C, Ferrand T, Chambost J, Wouters K, Malmsten J, Miller R, Zaninovic N, Vasconcelos F, Hickman C. He C, et al. Among authors: chambost j. Reprod Biomed Online. 2024 Mar;48(3):103654. doi: 10.1016/j.rbmo.2023.103654. Epub 2023 Nov 3. Reprod Biomed Online. 2024. PMID: 38246064 Free PMC article.

6

Backbone H(N), N, Calpha, C' and Cbeta assignment of the 25 kDa peptide methionine sulfoxide reductase from Erwinia chrysanthemi.

Béraud S, Chambost JP, Bersch B, Gans P, Barras F, Marion D. Béraud S, et al. Among authors: chambost jp. J Biomol NMR. 2001 May;20(1):97-8. doi: 10.1023/a:1011273109992. J Biomol NMR. 2001. PMID: 11430764 No abstract available.

7

The minimal gene set member msrA, encoding peptide methionine sulfoxide reductase, is a virulence determinant of the plant pathogen Erwinia chrysanthemi.

Hassouni ME, Chambost JP, Expert D, Van Gijsegem F, Barras F. Hassouni ME, et al. Among authors: chambost jp. Proc Natl Acad Sci U S A. 1999 Feb 2;96(3):887-92. doi: 10.1073/pnas.96.3.887. Proc Natl Acad Sci U S A. 1999. PMID: 9927663 Free PMC article.

8

Nucleotide sequence and molecular characterization of pnlA, the structural gene for damage-inducible pectin lyase of Erwinia carotovora subsp. carotovora 71.

Chatterjee A, McEvoy JL, Chambost JP, Blasco F, Chatterjee AK. Chatterjee A, et al. Among authors: chambost jp. J Bacteriol. 1991 Mar;173(5):1765-9. doi: 10.1128/jb.173.5.1765-1769.1991. J Bacteriol. 1991. PMID: 1705542 Free PMC article.

9

The beta-glucosides metabolism in Erwinia chrysanthemi: preliminary analysis and comparison to Escherichia coli systems.

Barras F, el Hassouni M, Chambost JP, Chippaux M. Barras F, et al. Among authors: chambost jp. FEMS Microbiol Rev. 1989 Jun;5(1-2):143-7. doi: 10.1016/0168-6445(89)90018-1. FEMS Microbiol Rev. 1989. PMID: 2699245 Review. No abstract available.

10

Characterization of a new endoglucanase from Erwinia chrysanthemi.

Boyer MH, Cami B, Chambost JP, Magnan M, Cattanéo J. Boyer MH, et al. Among authors: chambost jp. Eur J Biochem. 1987 Jan 15;162(2):311-6. doi: 10.1111/j.1432-1033.1987.tb10602.x. Eur J Biochem. 1987. PMID: 3026806 Free article.

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