2025
1. H. Zhang, X. Zeng., Y. Yin., and Z.-J. Zhu*，Knowledge and Data-driven Two-layer Networking for Accurate Metabolite Annotation in Untargeted Metabolomics，Nature Communications, 2025, 16: 8118.
2. X. Chen†, R. He†, H. Xiong, R. Wang, Y. Yin, Y. Chen*, and Z.-J.Zhu*，Quantitative profiling of lipid transport between organelles enabled by subcellular photocatalytic labeling，Nature Chemistry, 2025, 17, 1534-1545.
3. Y. Zhang, J. Chen, N. Chen, H. Xiong, Z.-J. Zhu, D.Yang*, J. Ge* and J. Yu*，Dimerization and substrate recognition of human taurine transporter，Nature Communications, 2025, 16: 6163.
4. Z. Chen, X. Gu, H. Chen, H. Zhang, J. Liu, X. Yang, Y. Cai, M. Zhang, L. Yan, Y. Yang, B. Shan, Z.-J. Zhu, Y. Zhang, J. Gu*, and D. Xu*，RIPK1 senses S-adenosylmethionine scarcity to drive cell death and inflammation，Cell Metabolism, 2025, 37: 1732-1749.
5. Y. Gao, M. Luo, H. Wang, Z. Zhou, Y. Yin, R. Wang, B. Xing, X. Yang, Y. Cai*, and Z.-J. Zhu*，Charting unknown metabolic reactions by mass spectrometry-resolved stable-isotope tracing metabolomics，Nature Communications, 2025, 16: 5059.
6. B. Xing, R. Wang, T. Kou, W. Liu, and Z.‐J. Zhu*，Unraveling Tissue‐Specific Fatty Acid Biosynthesis and Inter‐Tissue Crosstalk in Mice through Stable‐Isotope Tracing Metabolomics，Advanced Science, 2025, 12, 31, e03662.
7. X. Yang, T. Kou, H. Wang, J. Zhu, Z.-J. Zhu, and Y. Cai*，S-adenosylmethionine metabolism shapes CD8+ T cell functions in colorectal cancer，Cancer & Metabolism, 2025, 13: 23.
8. H. Liu, X. Chen, H. Wang, G.Zhuang, Z.-J. Zhu*, and M. Zhuang*，ZBTB17/MIZ1 promotes peroxisome biogenesis by transcriptional regulation of PEX13，Journal of Cell Biology, 2025, 224, e202407198.
9. Z. Xie, M. Lin, B. Xing, H. Wang, H. Zhang, Z. Cai, X. Mei*, and Z.-J. Zhu*，Citrulline regulates macrophage metabolism and inflammation to counter aging in mice，Science Advances, 2025,11, ads4957.
10. P. Wang, H. Ouyang, G. Bi, F. Liang, S. Hu, C. Wu, X. Jiang, W. Zhou, D. Li, S. Zhang, X. Yang, M. Zhao, J. Fang, H. Wang, W. Jia, Z.J. Zhu* and H. Bi*，Schisandrol B alleviates depression-like behavior in mice by regulating bile acid homeostasis in the brain-liver-gut axis via the pregnane X receptor，Phytomedicine, 2025, 137:156340.
2024
11. T. Zhang, W. Fu, H. Zhang, J. Li, B. Xing, Y. Cai, M. Zhang, X. Liu, C. Qi, L. Qian, X. Hu, H. Zhu, S. Yang, M. Zhang, J. Liu, G. Li, Y. Li, R. Xiang, Z. Qi, J. Hu, Y. Li, C. Zou, Q. Wang, X. Jin, R. Pang, P. Li, J. Liu, Y. Zhang, Z. Wang, Z.-J. Zhu*, B. Shan* and J. Yuan*，Spermidine mediates acetylhypusination of RIPK1 to suppress diabetes onset and progression，Nature Cell Biology, 2024, 26, 2099-2114.
12. J. Yan, X. Zhang, H. Wang, X. Jia, R. Wang, S. Wu, Z.-J. Zhu, M. Tan, and T. Horng*
Macrophage NRF1 promotes mitochondrial protein turnover via the ubiquitin proteasome system to limit mitochondrial stress and inflammation，Cell Reports, 2024, 43: 114780
13. Y. Yin, M. Luo, and Z.-J. Zhu*，Met4DX: a unified and versatile data processing tool for multi-dimensional untargeted metabolomics data，J. Am. Soc. Mass Spectrom., 2024, 35,2960-2968.
14. Y. Cai, X. Chen, F. Ren, H. Wang, Y. Yin, and Z.-J. Zhu*，Fast and broad-coverage lipidomics enabled by ion mobility-mass spectrometry，Analyst, 2024, 149, 5063-5072.
15. J. Lv†, C. Pan†, Y. Cai†, X. Han, C. Wang, J. Ma, J. Pang, F. Xu, S. Wu, T. Kou, F. Ren, Z.-J. Zhu*, T. Zhang*, J. Wang* and Y. Chen*，Plasma metabolomics reveals the shared and distinct metabolic disturbances associated with cardiovascular events in coronary artery disease，Nature Communications, 2024,15: 5729.
16. Y. Yang, H. Fang, Z. Xie, F. Ren, L. Yan, M. Zhang, G. Xu, Z. Song, Z. Chen, W. Sun, B. Shan, Z.-J. Zhu, and Daichao Xu*，Yersinia infection induces glucose depletion and AMPK-dependent inhibition of pyroptosis in mice，Nature Microbiology, 2024, 9, 2144–2159.
17. C. Zhao†, J. Tu†, C. Wang†, W. Liu, J. Gu, Y. Yin, S. Zhang, D. Li, J. Diao*, Z.-J. Zhu* and C. Liu*，Lysophosphatidylcholine binds α-synuclein and prevents its pathological aggregation，National Science Review, 2024, nwae182.
18. R. Xu, Y. Ning, F. Ren, C. Gu, Z.J. Zhu, X. Pan, A.V. Pshezhetsky*, J. Ge*, and J. Yu*，Structure and mechanism of lysosome transmembrane acetylation by HGSNAT，Nature Structural & Molecular Biology, 2024, 31, 1502-1508.
19. B. Yin†, Y. Cai†, T. Teng†, X. Wang, X. Liu, X. Li, Jie Wang, H. Wu, Y. He, F. Ren, T. Kou, Z.-J. Zhu* and X. Zhou*，Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents，Translational Psychiatry, 2024, 14: 163.
20. Y. Sun†, W. Liu†, M. Su, T. Zhang, X. Li, W. Liu, Y. Cai, D. Zhao, M. Yang, Z-J. Zhu*, J. Wang* and J. Yu*，Purine salvage–associated metabolites as biomarkers for early diagnosis of esophageal squamous cell carcinoma: a diagnostic model–based study，Cell Death Discovery, 2024, 10: 139.
21. Y. Bai†, T. Li†, Q. Wang†, W. You†, H. Yang, X. Xu, Z. Li, Y. Zhang, C. Yan, L. Yang, J. Qiu, Y. Liu, S. Chen, D. Wang, B. Huang, K.Liu, B.-L. Song, Z. Wang, K. Li, X. Liu, G. Wang, W. Yang, J. Chen, P Hao, Z. Zhang, Z. Wang*, Z.-J. Zhu* and C. Xu*，Shaping immune landscape of colorectal cancer by cholesterol metabolites，EMBO Molecular Medicine, 2024, 16, 334-360.
2023
22. H. Peng†, J.-Q. Qiu†, Q. Zhou†, Y. Zhang†, Q. Chen, Y. Yin, W. Su, S. Yu, Y. Wang, Y. Cai, M.Gu, H. Zhang, Q. Sun, G. Hu, Y. Wu, J. Liu, S. Chen*, Z.-J. Zhu*, X. Song*, and J. Zhou*，Intestinal epithelial dopamine receptor signaling drives sex-specific disease exacerbation in a mousemodel of multiple sclerosis，Immunity, 2023, 56, 2773-2789.
23. S. Chen, Y. Wu, Y. Gao, C. Wu, Y. Wang, C. Hou, M. Ren, S. Zhang, Q. Zhu, J. Zhang, Y. Yao, M. Huang, Y. B. Qi, X.-S. Liu, T. Horng, H. Wang, D. Ye, Z.-J. Zhu*, S. Zhao* and G. Fan*，Allosterically inhibited PFKL via prostaglandin E2 withholds glucose metabolism and ovarian cancer invasiveness，Cell Reports, 2023, 42, 113246.
24. Y. Lai, C. Zhao, Z. Tian, C. Wang, J. Fan, X. Hu, J. Tu, T. Li, J. Leitz, R.A. Pfuetzner, Z. Liu, S. Zhang, Z.Su, J. Burré, D. Li, T. C. Südhof, Z.-J. Zhu, C.Liu*, A. T. Brunger*, and J. Diao*，Neutral lysophosphatidylcholine mediates α-synuclein-induced synaptic vesicle clustering，PNAS, 2023, 120: e2310174120
25. H. Zhang, M. Luo, H. Wang, F. Ren, Y. Yin, and Z.-J. Zhu*，AllCCS2: Curation of Ion Mobility Collision Cross-Section Atlas for Small Molecules Using Comprehensive Molecular Representations，Analytical Chemistry, 2023, 95, 13913–13921.
26. F. Zhang, B. Zhang, H. Ding, X. Li, X. Wang, X. Zhang, Q. Liu, Q. Feng, M. Han, L. Chen, L. Qi, D. Yang, X. Li, X. Zhu, Q. Zhao, J. Qiu, Z. J. Zhu, H. Tang, N. Shen*, H. Wang*, and B. Wei*，The Oxysterol Receptor EBI2 Links Innate and Adaptive Immunity to Limit IFN Response and Systemic Lupus Erythematosus，Advanced Science, 2023: 2207108.
27. C. Yan, L. Zheng, S. Jiang, H. Yang, J. Guo, L.Jiang, T. Li, H. Zhang, Y. Bai, Y. Lou, Q. Zhang, T. Liang, W.g Schamel, H. Wang, W. Yang, G. Wang, Z.-J. Zhu, B.-L. Song*, and C. Xu* ,Exhaustion-associated cholesterol deficiency dampens the cytotoxic arm of antitumor immunity, Cancer Cell, 2023, https://doi.org/10.1016/j.ccell.2023.04.016
28. H. Wang, Y. Yin,and Z.-J. Zhu*, Encoding LC−MS-based Untargeted Metabolomics Data into Images towards AI-based Clinical Diagnosis, Analytical Chemistry, 2023, 95, 6533-6541.
29. M. Luo, Y. Yin, Z. Zhou, H. Zhang, X. Chen, H. Wang, and Z.-J. Zhu* ,A Mass Spectrum-oriented Computational Method for Ion Mobility-resolved Untargeted Metabolomics, Nature Communications, 2023, 14: 1813.
30. J. Wang, S. Zhou, ... W. Liu, J. Zhang, C. Peng, Z.-J. Zhu, M. Huang, Y. Li*, G. Zhuang*, and L. Tan*,Selective Covalent Targeting of Pyruvate Kinase M2 Using Arsenous Warheads, Journal of Medicinal Chemistry, 2023, 66, 2608-2621.
31. K. Niu, J. Zhang, S. Ge, D. Li, K. Sun, Y. You, J. Qiu, K. Wang, X. Wang, R. Liu, Y. Liu, B. Li, Z.-J. Zhu, L. Qu*, H.Jiang*, and N. Liu*, ONE-seq: epitranscriptome and gene-specific profiling of NAD-capped RNA, Nucleic Acids Research, 2023, 51: e12.
32. Y. Cai, Z. Zhou, and Z.-J. Zhu*,Advanced Analytical and Informatic Strategies for Metabolite Annotation in Untargeted Metabolomics, Trends in Analytical Chemistry, 2023, 158: 116903.
2022
33. H. Wang†, H. Jia†, Y. Gao, H. Zhang, J. Fan, L. Zhang, F. Ren, Y. Yin, Y. Cai*, J. Zhu*, and Z.-J. Zhu*,Serum Metabolic Traits Reveal Therapeutic Toxicities and Responses of Neoadjuvant Chemoradiotherapy in Patients with Rectal Cancer, Nature Communications, 2022, 13: 7802.
34. Z. Zhou†, M. Luo†, H. Zhang, Y. Yin, Y. Cai, and Z.-J. Zhu* (Corresponding author) ,Metabolite Annotation from Knowns to Unknowns through Knowledge-guided Multi-layer Metabolic Networking, Nature Communications, 2022, 13: 6656.
35. W. Liu, W. Zhang*, T. Li, Z. Zhou, M. Luo, X. Chen, Y. Cai*, and Z.-J. Zhu* (Corresponding author), Four-dimensional Untargeted Profiling of N-acylethanolamine Lipids in the Mouse Brain Using Ion Mobility-Mass Spectrometry, Analytical Chemistry, 2022, 94, 12472-12480.
36. J. Li, Y. Cao, K. Niu, J. Qiu, H. Wang, Y. You, D. Li, Y. Luo, Z. J. Zhu, Y. Zhang*, and N. Liu* ,Quantitative Acetylomics Reveals Dynamics of Protein Lysine Acetylation in Mouse Livers During Aging and Upon the Treatment of Nicotinamide Mononucleotide, Molecular and Cellular Proteomics, 2022, 21, 100276.
37. R. Wang, Y. Yin, J. Li, H. Wang, W. Lv, Y. Gao, T. Wang, Y. Zhong, Z. Zhou, Y. Cai, X. Su, N. Liu*, and Z.-J. Zhu* (corresponding author), Global Stable-isotope Tracing Metabolomics Reveals System-wide Metabolic Alternations in Aging Drosophila, Nature Communications, 2022, 13: 3518.
2021
38. X. Chen†, Y. Yin†, M. Luo, Z. Zhou, Y. Cai*, and Z.-J. Zhu* (corresponding author), Trapped Ion Mobility Spectrometry-Mass Spectrometry Improves the Coverage and Accuracy of Four-dimensional Untargeted Lipidomics, Analytica Chimica Acta, 2022, 1210: 339886.
39. X. Mei†, Y. Guo†, Z. Xie†, Y. Zhong, X. Wu, D. Xu, Y. Li, N. Liu, and Z.-J. Zhu* (corresponding author), RIPK1 Regulates Starvation Resistance by Modulating Aspartate Catabolism, Nature Communications, 2021, 12: 6144.
40. K. Deng, F. Zhao, Z. Rong, L. Cao, L. Zhang, K.Li*, Y. Hou*, and Z.-J. Zhu* (corresponding author), WaveICA 2.0: a novel batch effect removal method for untargeted metabolomics data without using batch information, Metabolomics, 2021, 17: 87
41. X. Shen, S. Wu, L. Liang, S. Chen, K. Contrepois, Z.-J. Zhu*(co-corresponding author), and M. Snyder*, metID: a R package for automatable compound annotation for LC−MS-based data, Bioinformatics, 2021, btab583.
42. H. Wang, W. Qi, C. Zou, Z. Xie, M. Zhang, M. Naito, L. Mifflin, Z. Liu, A. Najafov, H. Pan, B.Shan, Y. Li, Z.-J. Zhu, and J. Yuan*, NEK1-mediated Retromer Trafficking Promotes Blood–Brain Barrier Integrity by Regulating Glucose Metabolism and RIPK1 Activation, Nature Communications, 2021, 12: 4826
43. T. Li, Y. Yin, Z. Zhou, J. Qiu, W. Liu, X. Zhang, K. He, Y. Cai, and Z.-J. Zhu* (corresponding author), Ion Mobility-based Sterolomics Reveals Spatially and Temporally Distinctive Sterol Lipids in the Mouse Brain, Nature Communications, 2021, 12: 4343
44. X. Shen, C. Wang, N. Liang, Z. Liu, X. Li, Z.-J. Zhu, T. Merriman, N. Dalbeth, R.Terkeltaub, C. Li*, and H. Yin*, Serum metabolomics identifies dysregulated pathways and potential metabolic biomarkers for hyperuricemia and gout, Arthritis & Rheumatology, 2021, 73, 1738-1748.
45. J. Lv, J. Wang, X. Shen, J. Liu, D. Zhao, M. Wei, X. Li, B. Fan, Y. Sun, F. Xue, Z.-J. Zhu* (co-corresponding author), and T. Zhang*, A serum metabolomics analysis reveals a panel of screening metabolic biomarkers for esophageal squamous cell carcinoma, Clinical and Translational Medicine, 2021,11: e419.
46. J. Qiu†, T. Li†, and Z.-J. Zhu* (corresponding author), Multi-dimensional Characterization and Identification of Sterols in Untargeted LC-MS Analysis Using All Ion Fragmentation Technology, Analytica Chimica Acta, 2021, 1142, 108-117.
2020
47. Z. Li, J. Hou, Y. Deng, H. Zhi, W. Wu, B. Yan, T. Chen, J. Tu, Z.J. Zhu, W. Wu*, and D. Guo*, Exploring the Protective Effects of Danqi Tongmai Tablet on Acute Myocardial Ischemia Rats by Comprehensive Metabolomics Profiling, Phytomedicine, 2020, 74, 152918.
48. Y. You, Y. Gao, H. Wang, J. Li, X. Zhang, Z.-J. Zhu, and N. Liu*, Subacute Toxicity Study of Nicotinamide Mononucleotide via Oral Administration, Front. Pharmacol., 2020, 11: 604404.
49. X. Chen†, Y. Yin†, Z. Zhou, T. Li, and Z.-J. Zhu* (corresponding author), Development of A Combined Strategy for Accurate Lipid Structural Identification and Quantification in Ion-Mobility Mass Spectrometry based Untargeted Lipidomics, Analytica Chimica Acta, 2020, 1136, 115-124.
50. Z. Zhou, M. Luo, X. Chen, Y. Yin, X. Xiong, R. Wang, and Z.-J. Zhu* (corresponding author), Ion Mobility Collision Cross-Section Atlas for Known and Unknown Metabolite Annotation in Untargeted Metabolomics, Nature Communications, 2020, 11: 4334
51. 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*, A lipidome atlas in MS-DIAL 4, Nature Biotechnology, 2020, 38, 1159-1163.
52. M. Luo, Z. Zhou, and Z.-J. Zhu* (corresponding author), The Application of Ion Mobility-Mass Spectrometry in Untargeted Metabolomics: from Separation to Identification, Journal of Analysis and Testing, 2020, 4, 163-174.
53. Z. Rong, Q. Tan, L. Cao, L. Zhang, K. Deng, Y. Huang, Z.-J. Zhu, Z. Li, and K. Li*, NormAE: Deep Adversarial Learning Model to Remove Batch Effects in Liquid Chromatography Mass Spectrometry-Based Metabolomics Data, Analytical Chemistry, 2020, 92, 5082-5090.
54. 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*, Different Regions of Synaptic Vesicle Membrane Regulate VAMP2 Conformation for the SNARE Assembly, Nature Communications, 2020, 11: 1531.
55. Z. Yi, and Z.-J. Zhu* (corresponding author), Overview of Tandem Mass Spectral and Metabolite Databases for Metabolite Identification in Metabolomics, Methods in Molecular Biology, 2020, 2124, 139-148.
56. 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*, Daily Oscillation of the Excitation-Inhibition Balance in Visual Cortical Circuits, Neuron, 2020, 105, 621-629.
57. X. Chen, Z. Zhou, and Z.-J. Zhu* (Corresponding author), The Use of LipidIMMS Analyzer for Lipid Identification in Ion Mobility-Mass Spectrometry-Based Untargeted Lipidomics, Methods in Molecular Biology, 2020, 2084, 269-282.
2019
58. Y. Yin†, R. Wang †, Y. Cai, Z. Wang, and Z.-J. Zhu* (Corresponding Author), DecoMetDIA: Deconvolution of Multiplexed MS/MS Spectra for Metabolite Identification in SWATH-MS based Untargeted Metabolomics, Analytical Chemistry, 2019, 91, 11897-11904.
59. 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*, A Vitamin-C-derived DNA Modification Catalysed by An Algal TET Homologue, Nature, 2019, 569, 581–585.
60. X. Shen, R. Wang, X. Xiong, Y. Yin, Y. Cai, Z. Ma, N. Liu, and Z.-J. Zhu*(Corresponding Author), Metabolic Reaction Network-based Recursive Metabolite Annotation for Untargeted Metabolomics, Nature Communications, 2019, 10: 1516.
61. J. Tu†, Z. Zhou†,T. Li†, and Z.-J. Zhu* (Corresponding Author), The Emerging Role of Ion Mobility-Mass Spectrometry in Lipidomics to Facilitate Lipid Separation and Identification, Trends in Analytical Chemistry, 2019, 116, 332-339.
62. X. Shen, and Z.-J. Zhu*(Corresponding author), MetFlow: An Interactive and Integrated Workflow for Metabolomics Data Cleaning and Differential Metabolite Discovery, Bioinformatics, 2019, 35, 2870-2872.
63. R. Wang†, Y. Yin†, and Z.-J. Zhu* (Corresponding author), Advancing Untargeted Metabolomics Using Data Independent Acquisition Mass Spectrometry Technology, Analytical and Bioanalytical Chemistry, 2019, 411, 4235-4250.
64. K. Deng, F. Zhang, Q. Tan, Y. Huang, W. Song, Z. Rong, Z.-J. Zhu, K. Li*, and Z. Li*, WaveICA: A novel algorithm to remove batch effects for large-scale untargeted metabolomics data based on wavelet analysis, Analytica Chimica Acta, 2019, 1061, 60-69.
65. 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* (Co-Corresponding Author), Development of A Correlative Strategy to Discover Colorectal Tumor Tissue Derived Metabolite Biomarkers in Plasma Using Untargeted Metabolomics, Analytical Chemistry, 2019, 91, 2401-2408.
66. Z. Zhou, X. Shen, X. Chen, J. Tu, X. Xiong, and Z.-J. Zhu* (Corresponding Author), LipidIMMS Analyzer: Integrating Multi-dimensional Information to Support Lipid Identification in Ion Mobility–Mass Spectrometry based Lipidomics, Bioinformatics, 2019, 35, 698-700.
67. Y. Cai, and Z.-J. Zhu* (Corresponding author), A High-Throughput Targeted Metabolomics Workflow for the Detection of 200 Polar Metabolites in Central Carbon Metabolism, Methods in Molecular Biology, 2019, 1859，263-274.
2018
68. 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 Approach for Predicting Response to Neoadjuvant Chemotherapy for Colorectal Cancer, Metabolomics, 2018,14: 110.
69. Y. Cai, N. Liu*, and Z.-J. Zhu* (Co-Corresponding Author), Stable-isotope Labeled Metabolic Analysis in Drosophila melanogaster: From Experimental Setup to Data Analysis, Bio-protocol, 2018, 8(18): e3015.
70. H. Jia†, X. Shen†, Y. Guan, M. Xu, J. Tu, M. Mo, L. Xie, J. Yuan, J. Zhu*, and Z.J. Zhu*(Co-Corresponding author), Predicting the Pathological Response to Neoadjuvant Chemoradiation Using Untargeted Metabolomics in Locally Advanced Rectal Cancer, Radiotherapy and Oncology, 2018, 128, 548-556.
71. 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* (Co-Corresponding author), and N. Liu*, Epigenetic Drift of H3K27me3 in Aging Links Glycolysis to Healthy Longevity in Drosophila, eLife, 2018, 7: e35368.
72. H. Zha†, Y. Cai†, Y. Yin†, Z. Wang, K. Li, and Z.-J. Zhu* (Corresponding author), SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery, Analytical Chemistry, 2018, 90, 4062-4070.
73. J. Tu, Y. Yin, M. Xu, R. Wang, and Z.-J. Zhu*(Corresponding author), Absolute Quantitative Lipidomics Reveals Lipidome-Wide Alterations in Aging Brain, Metabolomics, 2018, 14: 5.
74. Z. Zhou†, J. Tu†, and Z.-J. Zhu*(Corresponding author), Advancing the Large-Scale CCS Database for Metabolomics and Lipidomics at the Machine-Learning Era, Current Opinion in Chemical Biology, 2018, 42, 34-41.
2017
75. 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.
76. 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.
77. 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.
78. 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.
79. 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.
80. 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.
2016
81. 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.