English Version

  • 邹权,电子科技大学基础与前沿研究院教授,博士研究生导师,IEEE高级会员,ACM高级会员,CCF杰出会员。
  • 常年招聘博士后,招聘科研助理,署名邮件必回复
  • 我对研究生的要求
  • 未经我允许,请不要给我寄送快递,尤其是各种礼物!如果您是我的学生,给我发封邮件告诉我近况,就是最美好的礼物!我的时间更想多看点书,而不是去取快递!

  • 研究方向:

  • 利用并行/高性能计算解决生物信息学问题
  • 利用机器学习方法解决生物信息学问题
  • 生物信息学应用问题

  • 主持项目:

    国家自然科学基金原创项目    支持生物序列机
    国家自然科学基金重点项目    面向单细胞RNA测序数据的深度迁移模型与细胞通信网络研究
    国家自然科学基金优秀青年基金    生物信息处理与分析
    四川省杰出青年科技人才项目    大规模生物序列分类和聚类方法研究
    国家自然科学基金面上项目    利用多序列比对指导16s rRNA的OTU聚类
    国家自然科学基金面上项目    基于MapReduce的非编码RNA“从头预测”识别方法研究 (已结题)
    国家自然科学基金青年基金    基于投票机制的非编码RNA“从头预测”识别方法研究 (已结题)
    福建省自然科学基金面上项目    转录组数据中的microRNA和SNP挖掘方法研究 (已结题)


  • Editor-in-Chief of Current Bioinformatics, Computers in Biology and Medicine
  • Co-Editor of Current Gene Therapy
  • Specialty Chief Editor of Computational Genomics (specialty section of Frontiers in Genetics)
  • Associate Editor of IEEE Access, Frontiers in Bioinformatics, Molecular Therapy-Nucleic Acids
  • Editorial Board Member of Briefings in Bioinformatics, Briefings in Functional Genomics, Computational Biology and Chemistry, Scientific Report, Interdisciplinary Sciences--Computational Life Sciences, Genes, Proteomics
  • Guest Associate Editor of PLoS Computational Biology

  • 出版著作:

  • Jon Galloway, Phil Haack, Brad Wilson等著. 孙远帅, 邹权译. ASP.NET MVC 4高级编程(第4版).清华大学出版社. 2013.8 ISBN:9787302330035
  • 系统生物学的网络分析方法. 邹权, 陈启安, 曾湘祥, 刘向荣 编著. 西安电子科技大学出版社. 2015.6. ISBN:9787560635385
  • Quan Zou (Ed.) Special Protein Molecules Computational Identification. MDPI. St. Alban-Anlage 66. Basel, Switzerland. ISBN: 9783038970439 (Pbk) 9783038970446 (PDF) doi:10.3390/books978-3-03897-044-6
  • Xiangxiang Zeng, Alfonso Rodríguez-Patón and Quan Zou (Eds.) Molecular Computing and Bioinformatics. MDPI. St. Alban-Anlage 66. Basel, Switzerland. ISBN 978-3-03921-195-1 (Pbk) ISBN 978-3-03921-196-8 (PDF) doi:10.3390/books978-3-03921-196-8

  • 特约报告:
  • 生物信息学中的不确定性和分类问题. CRSSC-CWI-CGrC2014青年学者论坛. 2014.8.7. 昆明. PPT
  • Machine learning and computational problems in genome-wide association study. CAAI机器学习专委会首届青年学者交流会. 2014.8.15. 南昌 PPT
  • Reconstructing phylogenetic trees for ultra-large unaligned DNA sequences via with Hadoop. The 9th International Conference on Systems Biology (ISB 2015). 2015.8.21. 洛阳 PPT
  • Computational prediction of miRNA and miRNA-disease relationship. 2015 Asian Conference on Membrane Computing (ACMC2015). 2015.11.14. 合肥 PPT
  • DNA多序列比对中的算法技术和并行方法. 2016大数据与精准生物医学信息学研讨会. 2016.3.26. 上海. PPT
  • Hierarchical learning and high dimensionality problems in bioinformatics. 中国人工智能学会机器学习专委会青年学者论坛. 2017.9.8. 西安 PPT
  • 基因序列的比对、挖掘和功能分析. 第二届中国计算机学会生物信息学会议. 2017.10.14. 长沙. PPT
  • 新的集成分类、降维策略与生物信息应用. 第九届全国生物信息学与系统生物学学术大会. 2020.9.28. 上海. PPT

  • 代表论文:

    1. Prediction of protein solubility based on sequence physicochemical patterns and distributed representation information with DeepSoluE. BMC Biology. 2023, 21:12. (web server)
    2. HAlign 3: fast multiple alignment of ultra-large numbers of similar DNA/RNA sequences. Molecular Biology and Evolution. 2022,39(8):msac166. (codes)
    3. webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study. Nucleic Acids Research. 2022, 50(D1): D1123-D1130. (web site)
    4. DeepBIO: An automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation, and visualization analysis. Nucleic Acids Research. Doi: 10.1093/nar/gkad055. (web server)
    5. A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data. PLoS Computational Biology. 2022, 18(9): e1010402 (codes)
    6. A comprehensive overview and evaluation of circular RNA detection tools. PLoS Computational Biology. 2017,13(6): e1005420 (SCI, IF2017=3.955, PMID: 28594838) (data and codes)(BibTeX, EndNote)
    7. Gene2vec: Gene Subsequence Embedding for Prediction of Mammalian N6‐Methyladenosine Sites from mRNA. RNA. 2019, 25(2): 205-218 (SCI, IF2017=4.490, PMID: 30425123) (web server)(BibTeX, EndNote)

    8. PaGeFinder: Quantitative Identification of Spatiotemporal Pattern Genes. Bioinformatics. 2012, 28(11):1544-1545. (SCI, IF2017=5.481, PMID:22492640)(Web Server)(BibTeX, EndNote)
    9. HAlign: Fast Multiple Similar DNA/RNA Sequence Alignment Based on the Centre Star Strategy. Bioinformatics. 2015,31(15): 2475-2481. (SCI, IF2017=5.481, PMID: 25812743) (Software)(该软件被OMICTOOLS推荐)(BibTeX, EndNote)
    10. Tumor Origin Detection with Tissue-Specific miRNA and DNA methylation Markers. Bioinformatics. 2018, 34(3): 398-406. (SCI, IF2017=5.481, PMID:29028927) (web server) (BibTeX, EndNote)
    11. O-GlcNAcPRED-II: an integrated classification algorithm for identifying O-GlcNAcylation sites based on fuzzy undersampling and a K-means PCA oversampling technique. Bioinformatics. 2018, 34(12): 2029-2036. (SCI, IF2017=5.481, PMID:29420699)(web server)(该软件被OMICTOOLS推荐)(BibTeX, EndNote)
    12. Prediction of potential disease-associated microRNAs using structural perturbation method. Bioinformatics. 2018, 34(14): 2425-2432.(SCI, IF2017=5.481, PMID:29490018)(codes)(BibTeX, EndNote)
    13. 4mCPred: Machine Learning Methods for DNA N4-methylcytosine sites Prediction. Bioinformatics. 2019, 35(4): 593-601 (SCI, IF2017=5.481, PMID: 30052767)(web server)(该软件被OMICTOOLS推荐)
    14. Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species. Bioinformatics. 2019, 35(8): 1326-1333. (SCI, IF2017=5.481, PMID: 30239627)(web server)
    15. PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning. Bioinformatics. 2019, 35(21):4272-4280. (SCI, IF2017=5.481, PMID:30994882) (web server)
    16. Iterative feature representations improve N4-methylcytosine site prediction. Bioinformatics. 2019, 35(23): 4930-4937. (SCI, IF2017=5.481, PMID:31099381)(web server)
    17. StackCPPred: A Stacking and Pairwise Energy Content based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency. Bioinformatics. 2020, 36(10):3028-3034. (code)
    18. PPTPP: A novel therapeutic peptide prediction method using physicochemical property encoding and adaptive feature representation learning. Bioinformatics. 2020, 36(13): 3982-3987 (codes and data)
    19. Basic polar and hydrophobic properties are the main characteristics that affect the binding of transcription factors to methylation sites. Bioinformatics. 2020,36(15):4263-4268 (Supplementary data)
    20. Identification of Sub-Golgi Protein Localization by Use of Deep Representation Learning Features. Bioinformatics. 2020, 36(24):5600-5609 (web server)
    21. BP4RNAseq: a babysitter package for retrospective and newly generated RNA-seq data analyses using both alignment-based and alignment-free quantification methods. Bioinformatics. 2021, 37(9):1319-1321. (codes) High impact research from Bioinformatics
    22. DeepAc4C: A convolutional neural network model with hybrid features composed of physico-chemical patterns and distributed representation information for identification of N4 acetylcytidine in mRNA. Bioinformatics. 2022, 38(1): 52-57. (web server)
    23. NerLTR-DTA: Drug-target binding affinity prediction based on neighbor relationship and learning to rank. Bioinformatics. 2022, 38(7): 1964-1971. (codes and datasets)
    24. GMNN2CD: Identification of circRNA–disease associations based on variational inference and graph Markov neural networks. Bioinformatics. 2022,38(8):2246-2253. (codes and data)
    25. webSCST: an interactive web application for single-cell RNA-sequencing data and spatial transcriptomic data integration. Bioinformatics. 2022, 38(13):3488-3489. (web server)
    26. Effector-GAN: prediction of fungal effector proteins based on pretrained deep representation learning methods and generative adversarial networks. Bioinformatics. 2022, 38(14):3541-3548. (web server)
    27. i6mA-Caps: A CapsuleNet-based framework for identifying DNA N6-methyladenine sites. Bioinformatics. 2022, 38(16): 3885-3891. (web server)

    28. Sequence clustering in bioinformatics: an empirical study. Briefings in Bioinformatics. 2020,21(1): 1-10 (SCI, IF2017=6.302, PMID: 30239587)(data) Highly Cited Articles from Briefings in Bioinformatics
    29. Prediction of bio-sequence modifications and the associations with diseases. Briefings in Functional Genomics. 2021, 20(1): 1-18 (data)Editor's Choice Highly Cited Articles from Briefings in Functional Genomics
    30. CPPred-RF: a sequence-based predictor for identifying cell-penetrating peptides and their uptake efficiency. Journal of Proteome Research.2017, 16(5):2044-2053. (SCI, IF2018=3.780)(web server)(入选ACS出版社庆祝中科院建院70周年Highlight文章)
    31. Prediction of human protein subcellular localization using deep learning. Journal of Parallel and Distributed Computing. 2018, 117: 212-217 (SCI, IF2017=1.815) most cited articles in this journal (BibTeX, EndNote)
    32. Review and comparative analysis of machine learning-based phage virion protein identification methods. BBA - Proteins and Proteomics. 2020,1868(6):140406 Featured in the BBA Collection on "Viruses" and "Artificial Intelligence for biochemistry and molecular biology: AI is learning to help"
    33. Multiple Sequence Alignment Based on a Suffix Tree and Center-Star Strategy: A Linear Method for Multiple Nucleotide Sequence Alignment on Spark Parallel Framework. Journal of Computational Biology. 2017, 24(12): 1230-1242 (SCI, IF2017=1.191, PMID: 29116822) (codes)(该软件被OMICTOOLS推荐)(BibTeX, EndNote)


  • 2021年度福建省自然科学奖三等奖(排名第2)
  • 2021年度黑龙江省自然科学二等奖(排名第2)
  • 2021年度天津市自然科学二等奖(排名第2)
  • 2020年第十届吴文俊人工智能自然科学奖二等奖(排名第2)
  • 2019年度福建省自然科学奖三等奖(排名第1)
  • 2019年度教育部自然科学奖二等奖(排名第2)
  • 2013年度厦门大学第七届高等教育教学成果二等奖(排名第5)
  • 第十三批四川省学术和技术带头人(自然科学)
  • 四川省高层次人才计划
  • 科睿唯安(Clarivate Analytics)“全球高被引学者”(2018, 2019, 2020, 2021, 2022)
  • 爱思唯尔2020中国高被引学者 (计算机科学与技术领域)
  • Global Peer Review Awards (Top 1% in Biology and Biochemistry, Cross-Field) Powered by Publons
  • 根据美国斯坦福大学发布的世界前2%科学家排名,截止2021年本人全球排名55392(2020年排名64999,2019年排名109706),其中生物信息学领域全球第30名(2020年第159名,2019年第346名),国内第3名(2020年第6名,2019年第14名);2021年单年引用全球排名第5946名(2020年第5915名,2019年第10929名),其中生物信息学领域全球第6名(2020年第23名,2019年第38名),国内第2名(2020年第3名,2019年第3名)(参考论文PLoS Biology 2020, 18(10): e3000918表S6和S7,数据链接)
  • Guide2Research计算机学科中国区学者排名第104名,世界第2149名(2021年2月数据)
  • 2022全球学者学术影响力排行榜第26758名
  • 《Frontiers of Computer Science》2019-2020年度“优秀青年AE”

  • 学术软件


  • 厦门大学
  • 天津大学
  • 电子科技大学

  • 联系方式:

  • Email: zouquan(a)nclab.net(为防止垃圾邮件,请把(a)换成@)
  • QQ:(同事请加32400920) (学生请加1020628735)

  • 最后修改时间:2023.1.18