Total Publications: 63

    Total Citations: >4,400

    H-index: 32

    Data from Google Scholar (update on December 2020) Web Link

  • 1. Multi-dimensional Characterization and Identification of Sterols in Untargeted LC-MS Analysis Using All Ion Fragmentation Technology

        J. Qiu†, T. Li†, and Z.-J. Zhu* (corresponding author),

        Analytica Chimica Acta, 2021, 1142, 108-117. Web Link

  • 2. Subacute Toxicity Study of Nicotinamide Mononucleotide via Oral Administration

        Y. You, Y. Gao, H. Wang, J. Li, X. Zhang, Z.-J. Zhu, and N. Liu*

        Frontiers in Pharmacology, 2020, 11, Article no. 604404. Web Link

  • 3. Development of A Combined Strategy for Accurate Lipid Structural Identification and Quantification in Ion-Mobility Mass Spectrometry based Untargeted Lipidomics

        X. Chen†, Y. Yin†, Z. Zhou, T. Li, and Z.-J. Zhu* (corresponding author)

        Analytica Chimica Acta, 2020, 1136, 115-124. Web Link

        Invited contribution for the Special Issue "Analytical Lipidomics"

  • 4. Ion Mobility Collision Cross-Section Atlas for Known and Unknown Metabolite Annotation in Untargeted Metabolomics

        Z. Zhou, M. Luo, X. Chen, Y. Yin, X. Xiong, R. Wang, and Z.-J. Zhu* (corresponding author)

        Nature Communications, 2020, 11: 4334. Web Link AllCCS Web

  • 5. A lipidome atlas in MS-DIAL 4

        H. Tsugawa , K. Ikeda, M. Takahashi , A. Satoh, Y. Mori, H. Uchino, N. Okahashi, Y. Yamada, I. Tada, P. Bonini, Y. Higashi, Y. Okazaki, Z. Zhou, Z.-J. Zhu, J. Koelmel, T. Cajka , O. Fiehn, K. Saito, M. Arita, and M. Arita*

        Nature Biotechnology, 2020, 38, 1159-1163. Web Link

  • 6. The Application of Ion Mobility-Mass Spectrometry in Untargeted Metabolomics: from Separation to Identification

        M. Luo, Z. Zhou, and Z.-J. Zhu* (corresponding author)

        Journal of Analysis and Testing, 2020, 4, 163-174. Web Link

        Invited review for the Special Issue "Metabolomics: state of art in method development and applications"

  • 7. NormAE: Deep Adversarial Learning Model to Remove Batch Effects in Liquid Chromatography Mass Spectrometry-Based Metabolomics Data

        Z. Rong, Q. Tan, L. Cao, L. Zhang, K. Deng, Y. Huang, Z.-J. Zhu, Z. Li, and K. Li*

        Analytical Chemistry, 2020, 92, 5082-5090. Web Link

  • 8. Different Regions of Synaptic Vesicle Membrane Regulate VAMP2 Conformation for the SNARE Assembly

        C. Wang, J. Tu, S. Zhang, B. Cai, Z. Liu, S. Hou, Q. Zhong, X. Hu, W. Liu, G. Li, Z. Liu, L. He, J. Diao, Z.-J. Zhu, Dan Li *, and C. Liu*

        Nature Communications, 2020, 11: 1531.  Web link

  • 9. Overview of Tandem Mass Spectral and Metabolite Databases for Metabolite Identification in Metabolomics

        Z. Yi, and Z.-J. Zhu* (corresponding author)

        Methods in Molecular Biology, 2020, 2124, 139-148. Web Link

        An invited book chapter for Computational Methods and Data Analysis for Metabolomics

  • 10. Daily Oscillation of the Excitation-Inhibition Balance in Visual Cortical Circuits

        M.C.D. Bridi, F. J. Zong, X. Min, N. Luo, T. Tran, J. Qiu, D. Severin, X.T. Zhang, G. Wang, Z.-J. Zhu, K.W. He,* and A. Kirkwood*

        Neuron, 2020, 105, 621-629.
  • 11. The Use of LipidIMMS Analyzer for Lipid Identification in Ion Mobility-Mass Spectrometry-Based Untargeted Lipidomics

        X. Chen, Z. Zhou, and Z.-J. Zhu* (Corresponding author)

        Methods in Molecular Biology, 2020, 2084, 269-282. Web Link
        An invited book chapter for Ion Mobility-Mass Spectrometry: Methods and Protocols

  • 12. DecoMetDIA: Deconvolution of Multiplexed MS/MS Spectra for Metabolite Identification in SWATH-MS based Untargeted Metabolomics

        Y. Yin†, R. Wang †, Y. Cai, Z. Wang, and Z.-J. Zhu* (Corresponding Author),

        Analytical Chemistry, 2019, 91, 11897-11904. Web Link

  • 13. A Vitamin-C-derived DNA Modification Catalysed by An Algal TET Homologue

    J. Xue†, G. Chen†, F. Hao†, H. Chen†, Z. Fang, F.-F. Chen, B. Pang, Q. Yang, X. Wei, Q. Fan, C. Xin, J. Zhao, X. Deng, B. Wang, X. Zhang, Y. Chu, H. Tang, H. Yin, W. Ma, L. Chen, J. Ding, E. Weinhold, R. M. Kohli, W. Liu, Z.-J. Zhu, K. Huang*, H. Tang* , and G.-L. Xu*

    Nature, 2019, 569, 581–585. Web Link

  • 14. Metabolic Reaction Network-based Recursive Metabolite Annotation for Untargeted Metabolomics

         X. Shen, R. Wang, X. Xiong, Y. Yin, Y. Cai, Z. Ma, N. Liu, and Z.-J. Zhu* (Corresponding Author)

         Nature Communications, 2019, 10: 1516. Web Link    MetDNA Webserver

  • 15. The Emerging Role of Ion Mobility-Mass Spectrometry in Lipidomics to Facilitate Lipid Separation and Identification

        J. Tu†, Z. Zhou†,T. Li†, and Z.-J. Zhu* (Corresponding Author),

        Trends in Analytical Chemistry, 2019, 116, 332-339. Web Link

        An invited contribution to the special issue of “Ion Mobility Spectrometry: From Fundamentals to Applications”.

  • 16. MetFlow: An Interactive and Integrated Workflow for Metabolomics Data Cleaning and Differential Metabolite Discovery

        X. Shen, and Z.-J. Zhu*(Corresponding author)

        Bioinformatics, 2019, 35, 2870-2872. Web Link Web Server Link


  • 17. Advancing Untargeted Metabolomics Using Data Independent Acquisition Mass Spectrometry Technology

        R. Wang†, Y. Yin†, and Z.-J. Zhu* (Corresponding author) ,

        Analytical and Bioanalytical Chemistry, 2019, 411, 4235-4250. Web Link

        An invited contribution to the special issue of “Young Investigators in Analytical and Bioanalytical Science”.

  • 18. WaveICA: A novel algorithm to remove batch effects for large-scale untargeted metabolomics data based on wavelet analysis

         K. Deng, F. Zhang, Q. Tan, Y. Huang, W. Song, Z. Rong, Z.-J. Zhu,  K. Li*, and Z. Li*, Analytica Chimica Acta, 2019, 1061, 60-69.

  • 19. Development of A Correlative Strategy to Discover Colorectal Tumor Tissue Derived Metabolite Biomarkers in Plasma Using Untargeted Metabolomics

        Z. Wang†, B. Cui†, F. Zhang, Y. Yang, X. Shen, Z. Li, W. Zhao, Y. Zhang, K. Deng, Z. Rong, K. Yang, X. Yu, K. Li*, P. Han*, and Z.-J. Zhu*

        Analytical Chemistry, 2019, 91, 2401-2408. Web Link (†, Co-first authors; *, Co-Corresponding authors)


  • 20. LipidIMMS Analyzer: Integrating Multi-dimensional Information to Support Lipid Identification in Ion Mobility–Mass Spectrometry based Lipidomics

        Z. Zhou, X. Shen, X. Chen, J. Tu, X. Xiong, and Z.-J. Zhu* (Corresponding Author)

        Bioinformatics, 2019, 35,698-700. Web Link LipidIMMS Web Server Link


  • 21. A High-Throughput Targeted Metabolomics Workflow for the Detection of 200 Polar Metabolites in Central Carbon Metabolism

        Y. Cai, and Z.-J. Zhu* (Corresponding author)

        Methods in Molecular Biology, 2019, 1859,263-274. Web Link An invited book chapter for Microbial Metabolomics

  • 22. Metabolomics Approach for Predicting Response to Neoadjuvant Chemotherapy for Colorectal Cancer

         K. Yang, F. Zhang, P. Han, Z. Z. Wang, K. Deng, Y. Y. Zhang, W. W. Zhao, W. Song, Y. Q. Cai, K. Li*, B. B. Cui, * and Z.J. Zhu*(Co-Corresponding author), Metabolomics, 2018,14: 110.

  • 23. Stable-isotope Labeled Metabolic Analysis in Drosophila melanogaster: From Experimental Setup to Data Analysis.

        Y. Cai, N. Liu*, and Z. J. Zhu* (Co-Corresponding Author)

        Bio-protocol, 2018, 8(18): e3015.Web Link

  • 24. Predicting the Pathological Response to Neoadjuvant Chemoradiation Using Untargeted Metabolomics in Locally Advanced Rectal Cancer

         H. Jia†, X. Shen†, Y. Guan, M. Xu, J. Tu, M. Mo, L. Xie, J. Yuan, J. Zhu*, and Z.J. Zhu*(†, Co-first authors; *, Co-Corresponding authors)

         Radiotherapy and Oncology, 2018, 128, 548-556. Web Link

  • 25. Epigenetic Drift of H3K27me3 in Aging Links Glycolysis to Healthy Longevity in Drosophila

        Z. Ma†, H. Wang†, Y. Cai†, H. Wang†, K. Niu, X. Wu, H. Ma, Y. Yang, W. Tong, F. Liu, Z. Liu, Y. Zhang, R. Liu, Z.-J. Zhu*, and N. Liu*

        eLife, 2018, 7: e35368 Web Link (†, Co-first authors; *, Co-Corresponding authors)Preprint at BioRxiv (

        --- This paper is highlighted by Science: "Epigenetics, aging, and glycolysis" Web Link

  • 26. SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery

        H. Zha†, Y. Cai†, Y. Yin†, Z. Wang, K. Li, and Z.-J. Zhu* (†, Co-first authors; *, Corresponding author)

        Analytical Chemistry, 2018, 90, 4062-4070. Web Link

  • 27. Absolute Quantitative Lipidomics Reveals Lipidome-Wide Alterations in Aging Brain

        J. Tu, Y. Yin, M. Xu, R. Wang, and Z.-J. Zhu*(Corresponding author)

        Metabolomics, 2018,14: 5. Web Link

  • 28. Advancing the Large-Scale CCS Database for Metabolomics and Lipidomics at the Machine-Learning Era

       Z. Zhou†, J. Tu†, and Z.-J. Zhu* (†, Co-first authors; *,Corresponding author)

       Current Opinion in Chemical Biology, 2018, 42, 34-41. (Invited Review) Web Link Recommended by F1000

  • 29. R. Lin*, Y. Mo, H. H. Zha, Z. Qu, P. Xie, Z.-J. Zhu, Y. Xu, Y. Xiong*, K.-L.Guan*,CLOCK Acetylates ASS1 to Drive Circadian Rhythm of Ureagenesis, Molecular Cell, 2017, 68, 198–209.
  • 30. X.Yang, Z. Wang, L. Guo, Z.-J. Zhu, and Y. Zhang*, Proteome-Wide Analysis of N-Glycosylation Stoichiometry Using SWATH Technology, Journal of Proteome Research, 2017, 16, 3830–3840.
  • 31. Z. Zhou, J. Tu, X. Xiong, X. Shen, and Z.-J. Zhu*(Corresponding author), LipidCCS: Prediction of Collision Cross-Section Values for Lipids with High Precision to Support Ion Mobility-Mass Spectrometry based Lipidomics, Analytical Chemistry, 2017, 89, 9559–9566. Web Link for Publication Web Link for LipidCCS Server

  • 32. Z. Zhou, X. Xiong, and Z.-J. Zhu* (Corresponding author), MetCCS Predictor: A Web Server for Predicting Collision Cross-Section Values of Metabolites in Metabolomics, Bioinformatics, 2017, 33, 2235-2237. Web Link for Publication Web Link for MetCCS Server

  • 33. J. Lu, B. Chen, T. T. Chen, S. Guo, X. Xue, Q. Chen, M. Zhao, L. Xia, Z. J. Zhu, L. Zheng*,  H. Yin*,Comprehensive Metabolomics Identified Lipid Peroxidation as A Prominent Feature in Human Plasma of Patients with Coronary Heart Diseases, Redoxy Biology,2017,12,899-907. Web Link
  • 34. M. Wang, Y. Fang, S. Gu, F. F. Chen, Z. J. Zhu, X. Sun*, J. Zhu*, Discovery of novel 1,2,3,4-tetrahydrobenzo[4, 5]thieno[2, 3-c]pyridine derivatives as potent and selective CYP17 inhibitors, European Journal of Medicinal Chemistry, 2017, 132, 157-172.
  • 35. Z. Zhou, X. Shen, J. Tu, and Z.-J. Zhu* (Corresponding author), Large-Scale Prediction of Collision Cross-Section Values for Metabolites in Ion Mobility - Mass Spectrometry, Analytical Chemistry, 2016, 88, 11084-11091. Web Link

  • 36. H. Li, Y. Cai, Y. Guo, F. Chen, and Z.-J. Zhu*(Corresponding author), MetDIA: Targeted Metabolite Extraction of Multiplexed MS/MS Spectra Generated by Data-Independent Acquisition, Analytical Chemistry, 2016, 88, 8757-8764. Web Link

  • 37. J. Wang*,†, T. Zhang†, X. Shen†, J. Liu, D. Zhao, Y. Sun, L. Wang, Y. Liu, X. Gong, Y. Liu, Z.-J. Zhu* (Co-corresponding author), F. Xue,*  Serum Metabolomics for Early Diagnosis of Esophageal Squamous Cell Carcinoma by UHPLC-QTOF/MS, Metabolomics, 2016, 12: 116 (*, Co-corresponding authors; †, Co-first authors) Web Link
  • 38. X. Shen, X. Gong, Y. Cai, Y. Guo, J. Tu, H. Li, T.Zhang, J. Wang, F. Xue, and Z.-J. Zhu* (Corresponding author),Normalization and Integration of Large-Scale Metabolomics Data Using Support Vector Regression, Metabolomics, 2016, 12: 89 Web Link
  • 39. Y. Cai, K. Weng, Y. Guo, J. Peng, and Z.-J. Zhu* (Corresponding author), An Integrated Targeted Metabolomic Platform for High-Throughput Metabolite Profiling and Automated Data Processing, Metabolomics, 2015,11,1575-1586. Web Link
  • 40. H.- G. Xia, A. Najafov,. J.Geng,. L. Galan-Acosta, X. Han,. Y. Guo, B. Shan, Y. Zhang, E. Norberg, T. Zhang, L.Pan, J.Liu, J. L. Coloff, D. Ofengeim, H. Zhu, K. Wu, Y. Cai, J. R. Yates, Z.- J. Zhu, J. Yuan, and H. Vakifahmetoglu-Norberg, Degradation of HK2 by Chaperone-Mediated Autophagy Promotes Metabolic Catastrophe and Cell Death, Journal of Cell Biology, 2015, 210,705-716.
  • 41. M. E. Kurczy, Z.-J. Zhu, ... 20 other authors..., G. Siuzdak*, Comprehensive Bioimaging with Fluorinated Nanoparticles Using Breathable Liquids, Nature Communications, 2015, 6, 5998.
  • 42. J. Ivanisevic, D. Elias, H. Deguchi, P.M. Averell, M. Kurczy, C. H. Johnson, R. Tautenhahn, Z.-J. Zhu, J. Watrous, M.Jain, J.Griffin, G.J. Patti  and G. Siuzdak*, Arteriovenous Blood Metabolomics: A Readout of Intra-Tissue Metabostasis, Scientific Reports, 2015, 5, 12757.
  • 43. C. Kim, G. Y. Tonga,B. Yan, C. S. Kim,S. T. Kim, M. H. Park,Z.-J. Zhu, B. Duncan,B. Creran, and V. M. Rotello*, Regulating Exocytosis of Nanoparticles via Host-guest Chemistry,Organic and Biomolecular Chemistry, 2015,13, 2474-2479.
  • 44. J. Ivanisevic, Z.-J. Zhu (Co-first author), L. Plate, R. Tautenhahn, S. Chen, P.J. O’Brien, C.H. Johnson, M. A. Marletta, G.J. Patti, and G. Siuzdak*, Toward 'Omic' Scale Metabolite Profiling: A Dual Separation – Mass Spectrometry Approach for Coverage of Lipid and Central Carbon Metabolism, Analytical Chemistry, 2013, 85, 6876–6884.
  • 45. Z.-J. Zhu, A.W. Schultz, J. Wang, C. H. Johnson, G. J. Patti, and G. Siuzdak*, Liquid Chromatography Quadrupole Time-of-Flight Characterization of Metabolites Guided by the METLIN Database, Nature Protocols, 2013, 8, 451-460.
  • 46. R. Tang, C. S. Kim, D. J. Solfiell, S. Rana, R. Mout, E. M. Velazquez-Delgado, A. Chompoosor, Y. Jeong, B. Yan, Z.-J. Zhu, C. Kim, J. A. Hardy, and V. M. Rotello*, Direct Delivery of Functional Proteins and Enzymes to the Cytosol Using Nanoparticle-Stabilized Nanocapsules, ACS Nano, 2013, 7, 6667-6673.
  • 47. B. Yan, Y. Jeong, L. A. Mercante, G. Y. Tonga, C. Kim, Z.-J. Zhu, R. W. Vachet*, and V. M. Rotello*, Characterization of surface ligands on functionalized magnetic nanoparticles using laser desorption/ionization mass spectrometry (LDI-MS), Nanoscale, 2013, 5, 5063-5066.
  • 48. R. Tautenhahn, K. Cho, W. Uritboonthai, Z.-J. Zhu, G. J. Patti, and G. Siuzdak*, An Accelerated Workflow for Untargeted Metabolomics Using the METLIN Database, Nature Biotechnology, 2012, 30, 826-828.
  • 49. Z.-J. Zhu, H. Wang, B. Yan, H. Zheng, Y. Jiang, O. R. Miranda, V. M. Rotello*, B. Xing*, and R. W. Vachet*, Effect of Surface Charge on the Uptake and Distribution of Gold Nanoparticles in Four Plant Species, Environmental Science and Technology, 2012, 22,12391-12398.
  • 50. Z.-J. Zhu, T. Posati, D. F. Moyano, R. Tang, B. Yan, R. W. Vachet*, and V. M. Rotello*, The Interplay of Monolayer Structure and Serum Protein Interactions on the Cellular Uptake of Gold Nanoparticles, Small, 2012, 8, 2659-2663.
  • 51. Z.-J. Zhu, R. Tang, Y.-C. Yeh, O. R. Miranda, V. M. Rotello*, and R. W. Vachet*, Determination of the Intracellular Stability of Gold Nanoparticle Monolayers Using Mass Spectrometry, Anal. Chem., 2012, 84, 4321-4326.
  • 52. Z.-J. Zhu, Y.-C. Yeh, R. Tang, R., B. Yan, Tamayo, J., R. W. Vachet*, and V. M. Rotello*, Stability of Quantum Dots in Live Cells, Nature Chemistry, 2011, 3, 963-968.
  • 53. O. R. Miranda, X. Li, L. Garcia-Gonzalez, Z.-J. Zhu, B. Yan, U. H. F. Bunz, and V. M. Rotello, Colorimetric Bacteria Sensing Using a Supramolecular Enzyme-Nanoparticle Biosensor, J. Am. Chem. Soc., 2011, 133, 9650-9653.
  • 54. X.-C. Yang, B. Samanta, S. S. Agasti, Y. Jeong, Z.-J. Zhu, S. Rana, O. R. Miranda, and V. M. Rotello*, Drug Delivery Using Nanoparticle‐Stabilized Nanocapsules, Angew. Chem., Int. Ed. 2011, 50, 477-481.
  • 55. C. K. Kim, S. S. Agasti, Z.-J. Zhu, L. Isaacs, and V. M. Rotello*, Host-Guest Chemistry inside Living Cells: Recognition-Mediated Activation of Therapeutic Gold Nanoparticles, Nature Chemistry, 2010, 2, 962-966.
  • 56. Z.-J. Zhu, R. Carboni, M. J. Quercio Jr., B. Yan, O. R. Miranda, D. L. Anderton, K. F. Arcaro*, V. M. Rotello*, and R. W. Vachet*, Surface Properties Dictate Uptake, Distribution, Excretion, and Toxicity of Nanoparticles in Fish, Small, 2010, 6, 2261-2265.
  • 57. A. Chompoosor, K. Saha, P. S. Ghosh, O. R. Miranda, Z.-J. Zhu, K. F. Arcaro, and V. M. Rotello*, The Role of Surface Functionality on Acute Cytotoxicity, ROS Generation and DNA Damage by Cationic Gold Nanoparticles, Small, 2010, 6, 2246-2249.
  • 58. P. Ghosh, X. Yang, R. Arvizo, Z.-J. Zhu, H. Mo, and V. M. Rotello*, Intracellular Delivery of a Membrane-Impermeable Enzyme in Active Form Using Functionalized Gold Nanoparticles, J. Am. Chem. Soc., 2010, 132, 2642–2645.
  • 59. B. Yan,Z.-J. Zhu, O. R. Miranda, A. Chompoosor, V. M. Rotello*, and R. W. Vachet*, Laser Desorption/Ionization Mass Spectrometry Analysis of Monolayer-protected Gold Nanoparticles, Anal. Bioanal. Chem., 2010, 396, 1025-1035.
  • 60. Z.-J. Zhu, V. M. Rotello*, and R. W. Vachet*, Engineered Nanoparticle Surfaces for Improved Mass Spectrometric Analyses, Analyst, 2009, 134, 2183-2188.
  • 61. C. K. Kim, P. Ghosh, C. Pagliuca, Z.-J. Zhu, S. Menichetti, and V. M. Rotello*, Entrapment of Hydrophobic Drugs in Nanoparticle Monolayers with Efficient Release into Cancer Cells, J. Am. Chem. Soc., 2009, 131, 1360–1361.
  • 62. Z.-J. Zhu, P. S. Ghosh, O. R. Miranda, R. W. Vachet*, and V. M. Rotello*, Multiplexed Screening of Cellular Uptake of Gold Nanoparticles Using Laser Desorption/Ionization Mass Spectrometry, J. Am. Chem. Soc., 2008, 130, 14139-14143.
  • 63. W.-Z. Jia, K. Wang, Z.-J. Zhu, H.-T. Song, and X.-H. Xia*, One-Step Immobilization of Glucose Oxidase in a Silica Matrix on a Pt Electrode by an Electrochemically Induced Sol-Gel Process, Langmuir, 2007, 23, 11896-11900.