Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Huaqiang Wen"'
Autor:
Jiahui Chen, Shuai Zhang, Genghua Chen, Xianqi Deng, Danlu Zhang, Huaqiang Wen, Yunqian Yin, Zetong Lin, Xiquan Zhang, Wen Luo
Publikováno v:
Animals, Vol 12, Iss 21, p 2956 (2022)
Chinese Shitou goose is a type of large goose with high meat yield. Understanding the genetic regulation of muscle development in Shitou goose would be beneficial to improve the meat production traits of geese. Muscle development is regulated by gene
Externí odkaz:
https://doaj.org/article/d223223df18e45ea8cf082bcf3c92920
Publikováno v:
Journal of Materials Chemistry A. 10:13266-13277
The electrocatalytic reaction mechanism and kinetics of CO2 reduction at the Ni–Fe dual-site were determined based on the grand canonical potential kinetics (GCP-K) method, and a new CO-passivating mechanism was revealed.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5b481b0487282c4e831a2d7aab55092
https://doi.org/10.1039/d2ta02931f
https://doi.org/10.1039/d2ta02931f
Transcriptome profile analysis reveals KLHL30 as an essential regulator for myoblast differentiation
Publikováno v:
Biochemical and Biophysical Research Communications. 559:84-91
Skeletal muscle development is a sophisticated multistep process orchestrated by diverse myogenic transcription factors. Recent studies have suggested that Kelch-like genes play vital roles in muscle disease and myogenesis. However, it is still uncle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::164147d9bee90157d3739e4604d85ae5
https://doi.org/10.1016/j.bbrc.2021.04.086
https://doi.org/10.1016/j.bbrc.2021.04.086
Publikováno v:
AIChE Journal. 68
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::417d472d35b7c5ea45f1a1ad1921223d
https://doi.org/10.1002/aic.17402
https://doi.org/10.1002/aic.17402
Quantitative structure-property relationship (QSPR) studies based on deep neural networks (DNN) are receiving increasing attention due to their excellent performances. A systematic methodology coupling multiple machine learning technologies is propos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::495581004e4d728ecfccf94d228aae52
https://doi.org/10.22541/au.162206662.29993062/v1
https://doi.org/10.22541/au.162206662.29993062/v1
Publikováno v:
Wang, Z, Wen, H, Su, Y, Shen, W, Ren, JI, Ma, Y & Li, J 2022, ' Insights into ensemble learning-based data-driven model for safety-related property of chemical substances ', Chemical Engineering Science, vol. 248, 117219 . https://doi.org/10.1016/j.ces.2021.117219
Risk assessment relying on characteristics of chemicals in process industries can prevent accidents caused by flammable and combustible liquids and gases. Whereas its application is limited by the lack of safety-related properties for abundant chemic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3ee3032c0b105ad8118f449ab7ae66cd
https://doi.org/10.1016/j.ces.2021.117219
https://doi.org/10.1016/j.ces.2021.117219