Chinese Version


    Dr. Quan Zou will be a Professor of Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China. He received his PH.D. from Harbin Institute of Technology, P.R.China in 2009, and worked at Xiamen University and Tianjin University from 2009 to 2018. His research is in the areas of bioinformatics, machine learning and parallel computing. Now he is putting the focus on protein classification, genome assembly, annotation and functional analysis from the next generation sequencing data with parallel computing methods. Several related works have been published by Briefings in Bioinformatics, Bioinformatics, PLOS Computational Biology and IEEE/ACM Transactions on Computational Biology and Bioinformatics. Google scholar showed that his more than 100 papers have been cited more than 4000 times. He is also a reviewer for many impacted journals and NSFC(National Natural Science Foundation of China).


1 Recruiting foreign post-doc
        Applicants should be less than 35 years old. I hope the applicants have published bioinformatics papers in Bioinformatics, NAR, PLoS CB, TCBB, BIB, or RECOMB. 3 more BMC/SR papers are also OK. My research is shown below. It is full time position. The salary is ~30,000 US dollar/year including tax. Publishing SCI papers would get more awards besides the salary. Interested applicants should send me the CV via email (zouquan@nclab.net) first, and notice in the title "[Postdoc application]".
2 Recruiting foreign PHD students
        I hope the applicants have published bioinformatics papers (SCI index). My research is shown below. It is full time position. It will cost 3-4 years for the PHD degree. There is no studying cost in my university. The applicants should try to apply CSC funding (http://www.campuschina.org/) from Chinese government. I will send recommendation letters to the applicants. But please send the CV to me first (zouquan@nclab.net), and notice in the title "[PHD application]".

Activity:

  • Clarivate Analytics Highly Cited Researchers 2018, 2019
  • Editor-in-Chief of Current Bioinformatics
  • Associate Editor of IEEE Access
  • Editorial Board Member of Computers in Biology and Medicine, Computational Biology and Chemistry, Scientific Report, Interdisciplinary Sciences--Computational Life Sciences, Genes
  • Guest Associate Editor of PLoS Computational Biology
  • Special issue guest editor for IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on NanoBioscience, Neurocomputing, Current Proteomics, BioMed Research International(1, 2), Current Genomics, Artificial Intelligence in Medicine, Computers & Electrical Engineering, Molecules(1, 2, 3), International Journal of Molecular Sciences, Current Gene Therapy, Genes, Mathematical Biosciences, Frontiers in Genetics(1, 2), Computing, Cells, Peer-to-Peer Networking and Applications, Combinatorial Chemistry & High Throughput Screening, IEEE Access, Journal of Electronic Science and Technology, The Chinese Journal of Electronics
  • Program Committee Chair of ICMHI2018
  • Organizing Committee Chair of BIIP2015, CHIP2017, BIIP2018
  • Publication Committee Chair of CCML2017
  • Publicity Chair of ISKE2017
  • Special Session Co-Chair of ISPACS2017
  • Keynote Speaker of ACMC2015, ICG2016
  • Special Session Organizer of IJCNN2016
  • Program Committee member of the CCIB2011 (Special Session on Computational Collective Intelligence in Bioinformatics, during the 3rd International Conference on Computational Collective Intelligence, ICCCI2011 Gdynia, Poland September 21-23, 2011); WAIM2014-2016 (International conference on Web-Age Information Management); FSDK2014(The 11th International Conference on Fuzzy Systems and Knowledge Discovery); ICIC2016(International Conference on Intelligent Computation); APWeb2016(Asia Pacific Web Conference); PRICAI2016(Pacific Rim International Conference on Artificial Intelligence); CCML2015; IJCNN2016(International Joint Conference on Neural Networks); ICMLC2016(International Conference on Machine Learning and Computing); GIW2016(The 27th International Conference on Genome Informatics); ISBRA2016(12th International Symposium on Bioinformatics Research and Applications); AAAI2017(31th AAAI Conference on Artificial Intelligence); AISTATS2017(20th International Conference on Artificial Intelligence and Statistics); NCIIP2017; ICYCSEE2017
  • Outstanding Reviewers for Computers in Biology and Medicine, Artificial Intelligence In Medicine, BBA - Molecular Basis of Disease, EBioMedicine, Journal of King Saud University - Computer and Information Sciences, Neurocomputing
  • Reviewer of Nature Methods, Nature Machine Intelligence, Nucleic Acids Research, Current Opinion in Structural Biology, Bioinformatics, Briefings in Bioinformatics, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Knowledge Discovery from Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Journal of Biomedical and Health Informatics, Cardiovascular Diabetology, BMC Bioinformatics, BMC Genomics, BMC System Biology, Oncogenesis, Oncotarget, Scientific Reports, SCIENCE CHINA Information Sciences, Journal of Computer Science and Technology, PLOS One, Molecular BioSystems, Amino Acids, Gene, Algorithms for Molecular Biology, Neural Networks, Journal of Theoretical Biology, Physica A, Computers in Biology and Medicine, Computational Biology and Chemistry, Physical Chemistry Chemical Physics, Journal of Cellular Biochemistry, Computer Methods and Programs in Biomedicine, Molecular Biology Reports, Functional & Integrative Genomics, Expert Systems, Biocybernetics and Biomedical Engineering, Neural Processing Letters, 3 Biotech, BioMed Research International, Current Bioinformatics, Protein & Peptide Letters, Computational and Mathematical Methods in Medicine, Acta Biotheoretica, Frontiers of Computer Science, Combinatorial Chemistry & High Throughput Screening, NIPS, ICML, IJCAI, AAAI, etc

  • Selected Papers:(*Corresponding author) Google Scholar

    1. 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)
    2. Details in the evaluation of circular RNA detection tools: Reply to Chen and Chuang. PLoS Computational Biology. 2019, 15(4): e1006916 (SCI, IF2017=3.955, PMID: 31022173)
    3. 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)

    4. 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)
    5. 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)
    6. 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) High impact research from Bioinformatics (BibTeX, EndNote)
    7. 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)
    8. 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)
    9. 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)
    10. 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)
    11. StackCPPred: A Stacking and Pairwise Energy Content based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency. Bioinformatics. Doi: 10.1093/bioinformatics/btaa131. (code)
    12. Iterative feature representations improve N4-methylcytosine site prediction. Bioinformatics. 2019, 35(23): 4930-4937. (SCI, IF2017=5.481, PMID:31099381)(web server)
    13. PaGeFinder: Quantitative Identification of Spatiotemporal Pattern Genes. Bioinformatics. 2012, 28(11):1544-1545. (SCI, IF2017=5.481, PMID:22492640)(Web Server)(BibTeX, EndNote)

    14. Sequence clustering in bioinformatics: an empirical study. Briefings in Bioinformatics. 2020,21(1): 1-10 (SCI, IF2017=6.302, PMID: 30239587)(data)
    15. Survey of MapReduce Frame Operation in Bioinformatics. Briefings in Bioinformatics. 2014,15(4): 637-647. (SCI, IF2017=6.302, PMID: 23396756)(BibTeX, EndNote)
    16. Integrative approaches for predicting microRNA function and prioritizing disease-related microRNA using biological interaction networks. Briefings in Bioinformatics. 2016,17(2):193-203.(SCI, IF2017=6.302, PMID:26059461)(BibTeX, EndNote)
    17. Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms. Briefings in Bioinformatics. 2020,21(1): 106-119. (SCI, IF2017=6.302, PMID:30383239)(web server)
    18. HITS-PR-HHblits: Protein remote homology detection by combining pagerank and hyperlink-induced topic search. Briefings in Bioinformatics. 2020,21(1): 298-308.(SCI, IF2017=6.302, PMID:30403770)(web server)
    19. Computational methods for identifying the critical nodes in biological networks. Briefings in Bioinformatics. Doi: 10.1093/bib/bbz011.(SCI, IF2017=6.302, PMID:30753282)
    20. Transcription factors-DNA interactions in rice: identification and verification. Briefings in Bioinformatics. doi: 10.1093/bib/bbz045(SCI, IF2017=6.302, PMID:31091308)
    21. Clustering and Classification Methods for Single-cell RNA-sequencing Data. Briefings in Bioinformatics. doi: 10.1093/bib/bbz062(SCI, IF2017=6.302, PMID:31271412)
    22. Critical evaluation of web-based prediction tools for human protein subcellular localization. Briefings in Bioinformatics. doi: 10.1093/bib/bbz106. (web server)
    23. Predicting Disease-associated Circular RNAs Using Deep Forests Combined with Positive-Unlabeled Learning Methods. Briefings in Bioinformatics. doi:10.1093/bib/bbz080.
    24. EP3: An ensemble predictor that accurately identifies type III secreted effectors. Briefings in Bioinformatics. Doi: 10.1093/bib/bbaa008. (web site)

    25. Fast prediction of protein methylation sites using a sequence-based feature selection technique. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2019,16(4):1264-1273. (SCI, IF2015=1.609, PMID:28222000)(web server)(该软件被OMICTOOLS推荐)
    26. Prediction and validation of disease genes using HeteSim Scores. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2017, 14(3):687-695. (SCI, IF2017=2.428, PMID:26890920)(Codes and Data)(BibTeX, EndNote)
    27. Inferring microRNA-disease associations by random walk on a heterogeneous network with multiple data sources. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2017, 14(4): 905-915.(Web Server)(SCI, IF2015=1.609, PMID:27076459)(BibTeX, EndNote)
    28. Improved and Promising Identification of Human MicroRNAs by Incorporating a High-quality Negative Set. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2014, 11(1):192-201 (SCI, IF2017=2.428, PMID: 24216114)(Software)(BibTeX, EndNote)
    29. Protein Complexes Identification with Family-Wise Error Rate Control. IEEE/ACM Transactions on Computational Biology and Bioinformatics. Doi: 10.1109/TCBB.2019.2912602. (SCI, IF2017=2.428, PMID:31027047)
    30. Advanced machine learning techniques for bioinformatics. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2019,16(4):1182-1183(SCI, IF2017=2.428)
    31. PhosPred-RF: a novel sequence-based predictor for phosphorylation sites using sequential information only. IEEE Transactions on NanoBioscience. 2017, 16(4): 240-247. (SCI, IF2017=2.158, PMID:28166503) (web server)(BibTeX, EndNote)
    32. Investigating maize yield-related genes in multiple omics interaction network data. IEEE Transactions on NanoBioscience. 2020, 19(1): 142-151 (SCI, IF2017=2.158, PMID:31170079)

    33. An overview of SNP interactions in genome-wide association studies. Briefings in Functional Genomics. 2015, 14(2):143-155. (SCI, IF2017=3.783,PMID: 25241224)(BibTeX, EndNote)
    34. Similarity computation strategies in the microRNA-disease network: A Survey. Briefings in Functional Genomics. 2016, 15(1): 55-64. (SCI, IF2017=3.783,PMID: 26134276) most cited articles in this journal (BibTeX, EndNote)
    35. Research Progress in Protein Post-Translational Modification Site Prediction. Briefings in Functional Genomics. 2018, 18(4): 220-229. (SCI, IF2017=3.783, PMID: 30576418)
    36. Deep learning in omics: a survey and guideline. Briefings in Functional Genomics. 2019, 18(1): 41-57 (SCI, IF2017=3.783, PMID: 30265280)
    37. Prediction of tumor metastasis from sequencing data in the era of genome sequencing. Briefings in Functional Genomics. 2019, 18(6): 412-418 (SCI, IF2017=3.783, PMID: 31204784)
    38. Machine learning and its applications in plant molecular studies. Briefings in Functional Genomics. 2020, 19(1): 40-48
    39. Identifying Cell Types to Interpret scRNA-seq Data: How, Why, and More Possibilities. Briefings in Functional Genomics. Doi: 10.1093/bfgp/elaa003

    40. 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)
    41. Local-DPP: An Improved DNA-binding Protein Prediction Method by Exploring Local Evolutionary Information. Information Sciences. 2017, 384:135-144. (SCI, IF2017=4.305)(web server)(BibTeX, EndNote)
    42. 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)
    43. 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)

    Contact:

  • Email: zouquan(a)nclab.net


  • Last modified: 2019-7-21