English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  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.

Item is

 

show all hide all

Basic

show hide
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

Files

show Files
hide Files
:
Article.pdf (Publisher version), 2MB
View   Save
File Permalink:
https://hdl.handle.net/21.11116/0000-0008-1872-D
Name:
Article.pdf
Description:
-
OA-Status:
Hybrid
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
View
Copyright Date:
-
Copyright Info:
-
License:
http://creativecommons.org/licenses/by/3.0/

Locators

show

Creators

show
hide
 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              

Content

show

Details

show
hide
Language(s): eng - English
 Dates: 2020-12-262021
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1039/D0SC06222G
DOI: 10.26434/chemrxiv.12357302.v1
BibTex Citekey: Moon2020
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Chemical Science
  Other : Chem. Sci.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Cambridge, UK : Royal Society of Chemistry
Pages: - Volume / Issue: 12 (8) Sequence Number: - Start / End Page: 2931 - 2939 Identifier: ISSN: 2041-6520