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  Predicting glycosylation stereoselectivity using machine learning

Moon, S.-Y., Chatterjee, S., Seeberger, P. H., & Gilmore, K. (2021). Predicting glycosylation stereoselectivity using machine learning. Chemical Science, 12(8), 2931-2939. doi:10.1039/D0SC06222G.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0006-7746-6 Version Permalink: https://hdl.handle.net/21.11116/0000-000B-068E-F
Genre: Journal Article

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 Creators:
Moon, Soo-Yeon1, Author           
Chatterjee, Sourav1, Author           
Seeberger, Peter H.2, Author           
Gilmore, Kerry1, Author           
Affiliations:
1Kerry Gilmore, Biomolekulare Systeme, Max Planck Institute of Colloids and Interfaces, Max Planck Society, ou_1863304              
2Peter H. Seeberger - Automated Systems, Biomolekulare Systeme, Max Planck Institute of Colloids and Interfaces, Max Planck Society, ou_1863306              

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Language(s): eng - English
 Dates: 2020-12-262021
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1039/D0SC06222G
DOI: 10.26434/chemrxiv.12357302.v1
BibTex Citekey: Moon2020
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Title: Chemical Science
  Other : Chem. Sci.
Source Genre: Journal
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Publ. Info: Cambridge, UK : Royal Society of Chemistry
Pages: - Volume / Issue: 12 (8) Sequence Number: - Start / End Page: 2931 - 2939 Identifier: ISSN: 2041-6520