From mechanism to application: Decrypting light-regulated denitrifying microbiome through geometric deep learning
Yang Liao , Jing Zhao , Jiyong Bian , Ziwei Zhang , Siqi Xu , Yijian Qin , Shiyu Miao , Rui Li , Ruiping Liu , Meng Zhang , Wenwu Zhu , Huijuan Liu , Jiuhui Qu
iMeta ›› 2024, Vol. 3 ›› Issue (1) : 162
From mechanism to application: Decrypting light-regulated denitrifying microbiome through geometric deep learning
•Graph neural networks (GNNs)-based biology-contextualized computational framework exhibited superior performance in identifying coexpressed gene panels and decrypting wavelength-dependent denitrification. •Wet-lab demonstrations validated the wavelength-divergent secretion system and nitrate-superoxide co-regulation as unveiled by GNNs, which could be utilized for nitrate removal and resource recovery. •The coexpressed gene panels and topological network toolkits were developed to guide scientific discovery and versatile biotechnology development.
denitrification / graph neural networks / meta-omics / microbiomes / optogenetics
2024 The Authors. iMeta published by John Wiley & Sons Australia, Ltd on behalf of iMeta Science.
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