Opportunities and Challenges of Predictive Approaches for the Non-coding RNA in Plants

Front Plant Sci. 2022 Apr 14:13:890663. doi: 10.3389/fpls.2022.890663. eCollection 2022.

Dong Xu^{1

2}, Wenya Yuan¹, Chunjie Fan³, Bobin Liu⁴, Meng-Zhu Lu¹, Jin Zhang¹

¹ State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou, China.
² Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
³ State Key Laboratory of Tree Genetics and Breeding, Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou, China.
⁴ Jiangsu Key Laboratory for Bioresources of Saline Soils, Jiangsu Synthetic Innovation Center for Coastal Bio-agriculture, School of Wetlands, Yancheng Teachers University, Yancheng, China.

No abstract available

Keywords: bioinformatics tools; deep learning; experimental technology; miRNA; non-coding RNA.