Zhang J., Yang L. B., Tian Z. Q., Zhao W. J., Sun C. Q., Zhu L. J., Huang M. J., Guo G., Liang G. Y. Large-Scale Screening of Antifungal Peptides Based on Quantitative Structure–Activity Relationship [J]. ACS Med. Chem. Lett., 2022, 13(1): 99-104.
Zhang, J.; Sun, X.; Zhao, H.; Zhou, X.; Zhang, Y.; Xie, F.; Li, B.; Guo, G*. In Silico Design and Synthesis of Antifungal Peptides Guided by Quantitative Antifungal Activity. J. Chem. Inf. Model. 2024, 64 (10), 4277–4285.
Transfer Learning
Zhang J., Zhou X, Li B. Y.*, PFCE2: A versatile parameter-free calibration enhancement framework for near-infrared spectroscopy, Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2023, 301: 122978.
Zhang J., Li B. Y., Hu Y., Zhou L. X., Wang G. Z., Guo G., Zhang Q. H., Lei S. C., Zhang A. H., A Parameter-Free Framework for Calibration Enhancement of Near-Infrared Spectroscopy Based on Correlation Constraint, Anal. Chim. Acta, 2021, 1142: 169-178.
Zhang J., Hu Y., Zhou L. X., Li B. Y.* Progress of Chemometric Algorithms in Near infrared Spectroscopic Analysis [J]. Journal of instrumental analysis, 2020, 39(10): 1196-1203.
Zhang J., Guo C., Cui X. Y., Cai W. S., Shao X. G.* A two-level strategy for standardization of near infrared spectra by multi-level simultaneous component analysis [J]. Analytica Chimica Acta, 2019, 1050: 25-31.
Zhang J., Cui X. Y., Cai W. S., Shao X. G.* Modified linear model correction: A calibration transfer method without standard samples [J]. NIR news, 2018, 29(8): 24-27.
Zhang J., Cai W. S., Shao X. G.*. New Algorithms for Calibration Transfer in Near Infrared Spectroscopy [J]. Progress in Chemistry, 2017, 29(8): 902-910.
Factor Analysis
Zhang J., Guo C.,Cai W. S., Shao X. G.* Direct non-trilinear decomposition for analyzing high-dimensional data with imperfect trilinearity [J]. Chemometrics and Intelligent Laboratory Systems, 2021, 210, 104244.
Zhang J., Peng Q. R., Xu L. Q., Yang M.*, Wu A. J., Ye S. Z. Application of three-way data analysis(second-order tensor decomposition)algorithms in analysis of liquid chromatography [J]. Chinese Journal of Chromatography, 2014, 32(11): 1165-1171.
Feature Selection
Zhang J., Cui X. Y., Cai W. S., Shao X. G.*. A variable importance criterion for variable selection in near-infrared spectral analysis [J]. Science China Chemistry, 2019, 62(2): 271-279.
Zhang J., Cui X. Y., Cai W. S., Shao X. G.* Combination of heuristic optimal partner bands for variable selection in near-infrared spectral analysis [J]. Journal of Chemometrics, 2018, 32(11): e2971.
Applications
Zhang J.†, Ma L.†, Li B. Y., et al. Identification of biomarkers for risk assessment of arsenicosis based on untargeted metabolomics and machine learning algorithms [J]. Science of the Total Environment, 2023, 870: 161861.
Zhang J.†, Yuan T.†, Wei S. X.†, Feng Z. H.†, Yang L. B., Huang H.. New strategy for clinical etiologic diagnosis of acute ischemic stroke and blood biomarker discovery based on machine learning[J]. RSC Adv., 2022, 12: 14716-14723.