植物与作物生物信息学分析

zouquan

研究成员

• 邹 权 (教授，电子科技大学)
• 曾湘祥（教授，湖南大学）
• 王彦苏（副研究员，电子科技大学）
• 王洁琛（博士后，电子科技大学）
• 沈子杰（博士后，电子科技大学）
  

承担项目

• 基于多组学大数据的植物基因组印记分析平台搭建，62402088，青年基金，荆晓彤主持
• 基于机器学习方法的土传真菌病害预测研究，62102269，青年基金，王彦苏主持
• 基于表型性状的植物耐旱性基因识别和筛选模型，62001088，青年，孙善文主持
  

组织专刊

• Jiacheng Wang, Yaojia Chen, Quan Zou*.Comparative Genomics and Functional Genomics Analysis in Plants. International Journalof Molecular Sciences. 2023, 24(7): 6539
• Shanwen Sun, Xiucai Ye*, Quan Zou*. Editorial: Machine Learning on Understanding theEpigenetic Mechanisms Underlying Plant Adaptation and Domestication. Frontiers in Plant Science. 2023, 14:1236787
• Yueqi Lu, QuanZou*. Functional Genomics and Comparative Genomics Analysis in Plants. CurrentIssues in Molecular Biology. 2024, 46: 13780-13782
• Shanwen Sun, Quan Zou*, Lijun Dou*. Editorial:Machine learning for mining plant functional genes. Frontiers in Plant Science. 2026, 17: 1795967
• Zhen Li, Ran Su, Qiangguo Jin, Quan Zou*. Editorial for Special Issue “Functional Genomics and Comparative Genomics Analysis in Plants, 3rd Edition”. Current Issues in Molecular Biology. 2026, 48: 394
  
  

发表论文

大豆相关

• LIU Yong-xin, HAN Ying-peng, CHANG Wei, ZOU Quan, GUO Mao-zu, LI Wen-bin.Genomic Analysis of MicroRNA Promoters and Their Cis-Acting Elements inSoybean. Agricultural Sciences in China.2010,9(11):1561-1570
• LIU Yong-xin, CHANG Wei, HAN Ying-peng, ZOU Quan, GUO Mao-zu, LI Wen-bin. Insilico Detection of Novel MicroRNAs Genes in Soybean Genome. Agricultural Sciences in China.2011,10(9): 1336-1345
• Yungang Xu, Maozu Guo, Quan Zou, XiaoyanLiu, Chunyu Wang, Yang Liu. System-level insights intothe cellular interactome of a non-model organism: inferring, modelling andanalysing functional gene network of Soybean (Glycine max). PLOS ONE. 2014,9(11):e113907
  
  

水稻相关

• Jing Jiang, Fei Xing, XiangxiangZeng, QuanZou*. RicyerDB: A Database For Collecting RiceYield-related Genes with Biological Analysis. International Journal of Biological Sciences. 2018,14(8):965-970
• Zijie Shen, Yuan Lin*, Quan Zou*. Transcription factors-DNA interactions in rice: identification and verification. Briefings in Bioinformatics. 2020, 21(3): 946-956
• Qianfei Huang, Jun Zhang, Leyi Wei, Fei Guo*, Quan Zou*. 6mA-RicePred: A method for identifying DNA N6-methyladenine sites in the rice genome based on feature fusion. Frontiers in Plant Science. 2020, 11: 4
• Zheng Chen, Zijie Shen, Lei Xu, Da Zhao, Quan Zou*. Regulator network analysis of rice and maize yield- related genes. Frontiers in Cell and Developmental Biology. 2020, 8: 621464
• Zhibin Lv, Hui Ding, Lei Wang, Quan Zou*. A Convolutional Neural Network Using Dinucleotide One-hot Encoder for identifying DNA N6-Methyladenine Sites in the Rice Genome. Neurocomputing. 2021, 422:214-221
  
  

玉米相关

• Jing Jiang, Fei Xing, Chunyu Wang, Xiangxiang Zeng*, Quan Zou*. Investigation andDevelopment of Maize Fused Network Analysis with Multi-omics. Plant Physiology and Biochemistry.2019, 141: 380-387
• Jing Jiang, Fei Xing, Xiangxiang Zeng*, Quan Zou*. Investigating maizeyield-related genes in multiple omics interaction network data. IEEE Transactions on NanoBioscience. 2020,19(1): 142-151
• Da Zhao, Zheng Chen, Lei Xu*, Lijun Zhang, Quan Zou*. Genome-Wide Analysis of the MADS-Box Gene Family in Maize: Gene Structure, Evolution, and Relationships. Genes. 2021, 12: 1956
  
  

其他植物/作物

• Yong Huang, Quan Zou, Z.B. Wang. Computational Identification of miRNA Genes and Their Targets in Mulberry. Russian Journal of Plant Physiology. 2014, 61(4): 537-542
• Zheng Chen, Zijie Shen, Da Zhao, Lei Xu*, Lijun Zhang, Quan Zou*. Genome-wide analysis of LysM-containing gene family in Wheat: evolution and duplications during development and denfences. Genes. 2020, 12(1):31
• Xiaotong Jing, Quan Zou, Hui Yang*. Genome-Wide Identification and Characterization of the Aux/IAA Gene Family in Strawberry Species. Plants. 2024, 13: 2940
• Jiechen Wang, Jiaqi Song, Siyue Qi, Quan Zou, Hongzhen Liu, Huihui Zhang*, Xiaoqing Ru*. Genome-Wide Identification of the TGA transcription factor Family in Populus alba × Populus glandulosa and Functional Validation of PagTGA7b in Salt Tolerance. Plant Stress. 2026, 19: 101157
  
  

植物微生物

• Yansu Wang, Murong Zhou, Quan Zou, Lei Xu. Machine learning for phytopathology: from the molecular scale towards the network scale. Briefings in Bioinformatics. 2021, 22(5): bbab037
• Yansu Wang, Jie Wu, Jiacheng Yan, Ming Guo, Lei Xu, Liping Hou*, Quan Zou*. Comparative genome analysis of plant ascomycete fungal pathogens with different lifestyles reveals distinctive virulence strategies. BMC Genomics. 2022, 23:34
• Yansu Wang, Quan Zou*. Deep learning meta-analysis for predicting plant soil-borne fungal disease occurrence from soil microbiome data. Applied Soil Ecology. 2024, 202: 105532
  
  

泛植物

• Shanwen Sun, Chunyu Wang, Hui Ding, Quan Zou*. Machine learning and its applications in plant molecular studies. Briefings in Functional Genomics. 2020, 19(1): 40-48
• Changli Feng, Quan Zou*, Donghua Wang*. Using a Low Correlation High Orthogonality Feature Set and Machine Learning Methods to Identify Plant Pentatricopeptide Repeat Coding Gene/Protein. Neurocomputing. 2021, 424: 246-254
• Mengting Niu, Yuan Lin*, Quan Zou*. SgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks. Plant Molecular Biology. 2021, 105(4-5): 483-495
• Yansu Wang, Lei Xu, Quan Zou, Chen Lin*. prPred-DRLF: plant R protein predictor using deep representation learning features. Proteomics. 2022, 22(1-2) 202100161
• Shuwan Yin, Jia Zheng, Cangzhi Jia*, Quan Zou, Zhengkui Lin*, Hua Shi*. UPFPSR: a ubiquitylation predictor for plant through combining sequence information and random forest. Mathematical Biosciences and Engineering. 2022, 19(1): 775-791
• Shihu Jiao, Quan Zou*. Identification of plant vacuole proteins by exploiting deep representation learning features. Computational and Structural Biotechnology Journal. 2022, 20: 2921-2927
• Jinwei Wang, Zhenjie Luo, Aoyun Geng, Junlin Xu, Yajie Meng, Shankai Yan, Leyi Wei, Zilong Zhang, Qingchen Zhang, Quan Zou, Feifei Cui. DeepNhKcr: explainable deep learning framework for the prediction of crotonylation sites of non-histone lysine in plants based on pre-trained protein language model. IEEE Transactions on Computational Biology and Bioinformatics. 2026, 23(1): 326-340
• Xiaotong Jing, Xi Su, Quan Zou, Mengting Niu*. Bioinformatics insights into plant genomic imprinting: approaches, challenges, and future perspectives. Briefings in Functional Genomics. 2026, 25: elaf025