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Glycome informatics: using systems biology to gain mechanistic insights into glycan biosynthesis

Тип публикацииJournal Article
Дата публикации2021-06-01
scimago Q1
wos Q1
БС1
SJR1.571
CiteScore17.0
Impact factor6.8
ISSN22113398
General Energy
Краткое описание
Glycobiology entails the study of glycans, or carbohydrate sugar chains. Much research has been made in understanding individual glycogenes such as glycosyltransferases, and glycan structures using glycomics technologies. However, to get an overall understanding of the importance of glycosylation, current technologies are lacking, and systems biology approaches have recently been incorporated to gain better insight into glycosylation mechanisms and their applicability to biological function. Many databases organizing glycobiology data have been developed, and a variety of methods for mathematically modeling glycosylation pathways have shown to be effective. While it is known that glycans modulate signaling pathways, however, the future is wide open for systems glycobiology research.
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Aoki-Kinoshita K. F. Glycome informatics: using systems biology to gain mechanistic insights into glycan biosynthesis // Current Opinion in Chemical Engineering. 2021. Vol. 32. p. 100683.
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Aoki-Kinoshita K. F. Glycome informatics: using systems biology to gain mechanistic insights into glycan biosynthesis // Current Opinion in Chemical Engineering. 2021. Vol. 32. p. 100683.
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TY - JOUR
DO - 10.1016/j.coche.2021.100683
UR - https://doi.org/10.1016/j.coche.2021.100683
TI - Glycome informatics: using systems biology to gain mechanistic insights into glycan biosynthesis
T2 - Current Opinion in Chemical Engineering
AU - Aoki-Kinoshita, Kiyoko F.
PY - 2021
DA - 2021/06/01
PB - Elsevier
SP - 100683
VL - 32
SN - 2211-3398
ER -
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@article{2021_Aoki-Kinoshita,
author = {Kiyoko F. Aoki-Kinoshita},
title = {Glycome informatics: using systems biology to gain mechanistic insights into glycan biosynthesis},
journal = {Current Opinion in Chemical Engineering},
year = {2021},
volume = {32},
publisher = {Elsevier},
month = {jun},
url = {https://doi.org/10.1016/j.coche.2021.100683},
pages = {100683},
doi = {10.1016/j.coche.2021.100683}
}