Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Hung-Jui S. Shih"'
Autor:
Carly M. Shanks, Ji Huang, Chia-Yi Cheng, Hung-Jui S. Shih, Matthew D. Brooks, José M. Alvarez, Viviana Araus, Joseph Swift, Amelia Henry, Gloria M. Coruzzi
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
Nitrogen (N) and Water (W) - two resources critical for crop productivity – are becoming increasingly limited in soils globally. To address this issue, we aim to uncover the gene regulatory networks (GRNs) that regulate nitrogen use efficiency (NUE
Externí odkaz:
https://doaj.org/article/2a5a98b650b24810832a07c91dd50946
Autor:
Chia-Yi Cheng, Ying Li, Kranthi Varala, Jessica Bubert, Ji Huang, Grace J. Kim, Justin Halim, Jennifer Arp, Hung-Jui S. Shih, Grace Levinson, Seo Hyun Park, Ha Young Cho, Stephen P. Moose, Gloria M. Coruzzi
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-15 (2021)
Predicting complex phenotypes from genomic information is still a challenge. Here, the authors use an evolutionarily informed machine learning approach within and across species to predict genes affecting nitrogen utilization in crops, and show their
Externí odkaz:
https://doaj.org/article/df8c1a08be1a4c64bc07660726b1c1e2
Autor:
Ying Li, Grace Kim, Grace Levinson, Gloria M. Coruzzi, Chia Yi Cheng, Hung Jui S. Shih, Jessica Bubert, Kranthi Varala, Ha Young Cho, Ji Huang, Jennifer Arp, Justin Halim, Seo Hyun Park, Stephen P. Moose
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-15 (2021)
Nature Communications
Nature Communications
Inferring phenotypic outcomes from genomic features is both a promise and challenge for systems biology. Using gene expression data to predict phenotypic outcomes, and functionally validating the genes with predictive powers are two challenges we add
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b24ba54f201be254ac9b4e634c1797c
https://doaj.org/article/df8c1a08be1a4c64bc07660726b1c1e2
https://doaj.org/article/df8c1a08be1a4c64bc07660726b1c1e2