Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Yanqiao Zhu"'
Autor:
Yanqiao Zhu, Reena Narsai, Cunman He, Yan Wang, Oliver Berkowitz, James Whelan, Lim Chee Liew
Publikováno v:
Plant Communications, Vol 4, Iss 1, Pp 100501- (2023)
Mitochondrial retrograde signaling (MRS) supports photosynthetic function under a variety of conditions. Induction of mitochondrial dysfunction with myxothiazol (a specific inhibitor of the mitochondrial bc1 complex) or antimycin A (an inhibitor of t
Externí odkaz:
https://doaj.org/article/58c590dd5f38491797230b0519a1437d
Autor:
Yanqiao Zhu, Kai Yang
Publikováno v:
IEEE Access, Vol 7, Pp 63195-63203 (2019)
Most existing approaches to anomaly detection focus on statistical features of the data. However, in many cases, users are merely interested in a subset of the statistical outliers depending on the specific domain of interest, e.g., network attacks o
Externí odkaz:
https://doaj.org/article/5923a0b4c26c48b08ec4bd1b1c352081
Autor:
Siyi Zhao, Yanqiao Zhu, Wenwen Liu, Xiaoshan Wang, Han Wang, Yingping Cao, Fei Chen, Longxing Hu, Lixia Gong, Chunxiang Fu, Zhifei Zhang
Publikováno v:
PLoS ONE, Vol 16, Iss 10 (2021)
Excess copper (Cu) in soil due to industrial and agricultural practices can result in reduced plant growth. Excess Cu resulted in severely retarded root growth with severe discoloration of Alfalfa (Medicago sativa) and Medicago truncatula. Growth in
Externí odkaz:
https://doaj.org/article/c622264da54345bb8d5e99639d052189
Publikováno v:
Frontiers in Plant Science, Vol 7 (2016)
Flower development, pollination, and fertilization are important stages in the sexual reproduction process of plants; they are also critical steps in the control of seed formation and development. During alfalfa (Medicago sativa L.) seed production,
Externí odkaz:
https://doaj.org/article/06f272b59f5b4c698e42e04e310aa710
Publikováno v:
ACM Transactions on Intelligent Systems & Technology; Oct2023, Vol. 14 Issue 5, p1-21, 21p
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-14
Recent years have witnessed growing interests in multimedia recommendation, which aims to predict whether a user will interact with an item with multimodal contents. Previous studies focus on modeling user-item interactions with multimodal features i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a104254cc4294e54e99bc6c2ddf6dda3
https://doi.org/10.1109/tkde.2022.3221949
https://doi.org/10.1109/tkde.2022.3221949
Autor:
Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::401b51a09f4ed2ca45a67d0050b0b2fd
https://doi.org/10.1109/bigdata55660.2022.10020992
https://doi.org/10.1109/bigdata55660.2022.10020992
Autor:
Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7bb9289a8d9a81ce3d83c458794664c1
https://doi.org/10.1109/bigdata55660.2022.10020955
https://doi.org/10.1109/bigdata55660.2022.10020955
Autor:
Lim Chee Liew, Yanqiao Zhu, Yan Wang, Bhavna Hurgobin, Oliver Berkowitz, James Whelan, Mathew G. Lewsey, Yue Xu
Publikováno v:
The Plant Journal. 107:938-955
Acclimation of plants to adverse conditions requires the coordination of gene expression and signalling pathways between tissues and cell types. As the energy and carbon capturing organs, leaves are significantly affected by abiotic and biotic stress
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5be2da6ec4c715cc16b753bdb5241cae
https://doi.org/10.1111/tpj.15314
https://doi.org/10.1111/tpj.15314
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Brain networks characterize complex connectivities among brain regions as graph structures, which provide a powerful means to study brain connectomes. In recent years, graph neural networks have emerged as a prevalent paradigm of learning with struct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a550aa43e707e4756acf4393cf460c73
https://doi.org/10.1145/3534678.3542680
https://doi.org/10.1145/3534678.3542680