| Baseline correction using adaptive iteratively reweighted penalized least squares ZM Zhang, S Chen, YZ Liang Analyst 135 (5), 1138-1146, 2010 | 975 | 2010 |
| Deep-learning-based drug–target interaction prediction M Wen, Z Zhang, S Niu, H Sha, R Yang, Y Yun, H Lu Journal of proteome research 16 (4), 1401-1409, 2017 | 489 | 2017 |
| An intelligent background‐correction algorithm for highly fluorescent samples in Raman spectroscopy ZM Zhang, S Chen, YZ Liang, ZX Liu, QM Zhang, LX Ding, F Ye, H Zhou Journal of Raman Spectroscopy 41 (6), 659-669, 2009 | 352 | 2009 |
| Deep learning-based component identification for the Raman spectra of mixtures X Fan, W Ming, H Zeng, Z Zhang, H Lu Analyst 144 (5), 1789-1798, 2019 | 166 | 2019 |
| Application of random forests to select premium quality vegetable oils by their fatty acid composition F Ai, J Bin, Z Zhang, J Huang, J Wang, Y Liang, L Yu, Z Yang Food chemistry 143, 472-478, 2014 | 127 | 2014 |
| DeepMirTar: a deep-learning approach for predicting human miRNA targets M Wen, P Cong, Z Zhang, H Lu, T Li Bioinformatics 34 (22), 3781-3787, 2018 | 93 | 2018 |
| Morphological weighted penalized least squares for background correction Z Li, DJ Zhan, JJ Wang, J Huang, QS Xu, ZM Zhang, YB Zheng, YZ Liang, ... Analyst 138 (16), 4483-4492, 2013 | 90 | 2013 |
| Predicting a molecular fingerprint from an electron ionization mass spectrum with deep neural networks H Ji, H Deng, H Lu, Z Zhang Analytical chemistry 92 (13), 8649-8653, 2020 | 83 | 2020 |
| Prediction of liquid chromatographic retention time with graph neural networks to assist in small molecule identification Q Yang, H Ji, H Lu, Z Zhang Analytical Chemistry 93 (4), 2200-2206, 2021 | 82 | 2021 |
| Peak alignment using wavelet pattern matching and differential evolution ZM Zhang, S Chen, YZ Liang Talanta 83 (4), 1108-1117, 2011 | 80 | 2011 |
| Multiscale peak detection in wavelet space ZM Zhang, X Tong, Y Peng, P Ma, MJ Zhang, HM Lu, XQ Chen, YZ Liang Analyst 140 (23), 7955-7964, 2015 | 77 | 2015 |
| Calibration transfer via an extreme learning machine auto-encoder WR Chen, J Bin, HM Lu, ZM Zhang, YZ Liang Analyst 141 (6), 1973-1980, 2016 | 65 | 2016 |
| Multiscale peak alignment for chromatographic datasets ZM Zhang, YZ Liang, HM Lu, BB Tan, XN Xu, M Ferro Journal of Chromatography A, 2011 | 63 | 2011 |
| Deep MS/MS-aided structural-similarity scoring for unknown metabolite identification H Ji, Y Xu, H Lu, Z Zhang Analytical chemistry 91 (9), 5629-5637, 2019 | 59 | 2019 |
| Comprehensive metabolic profiles of seminal plasma with different forms of male infertility and their correlation with sperm parameters Y Xu, H Lu, Y Wang, Z Zhang, Q Wu Journal of Pharmaceutical and Biomedical Analysis 177, 112888, 2020 | 55 | 2020 |
| Representative subset selection and outlier detection via isolation forest WR Chen, YH Yun, M Wen, HM Lu, ZM Zhang, YZ Liang Analytical methods 8 (39), 7225-7231, 2016 | 53 | 2016 |
| Comparisons of five algorithms for chromatogram alignment W Jiang, ZM Zhang, YH Yun, DJ Zhan, YB Zheng, YZ Liang, ZY Yang, ... Chromatographia 76, 1067-1078, 2013 | 50 | 2013 |
| Baseline correction of high resolution spectral profile data based on exponential smoothing X Liu, Z Zhang, Y Liang, PFM Sousa, Y Yun, L Yu Chemometrics and Intelligent Laboratory Systems 139, 97-108, 2014 | 47 | 2014 |
| Synthesis of multi-Au-nanoparticle-embedded mesoporous silica microspheres as self-filtering and reusable substrates for SERS detection M Chen, W Luo, Z Zhang, R Wang, Y Zhu, H Yang, X Chen ACS applied materials & interfaces 9 (48), 42156-42166, 2017 | 45 | 2017 |
| Classification of green and black teas by PCA and SVM analysis of cyclic voltammetric signals from metallic oxide-modified electrode N Liu, Y Liang, J Bin, Z Zhang, J Huang, RX Shu, K Yang Food Analytical Methods 7, 472-480, 2014 | 44 | 2014 |
Yi-Zeng LiangProfessor of Analytical Chemistry and Chemometrics, Central South University在 csu.edu.cn 的电子邮件经过验证
