Citation: | Daotong Zhao, Chunguo Wang, Hanyun Qu, Qinling Rao, Bingqing Shen, Yinan Jiang, Jiayu Gong, Yumiao Wang, Di Geng, Rui Hong, Tao Lu, Qing Ni, Xinqi Deng. Glycomol: A pervasive tool for structure predication of natural saponin products basing on MS data[J]. Journal of Pharmaceutical Analysis, 2024, 14(7): 100897. doi: 10.1016/j.jpha.2023.11.004 |
[1] |
J. Cai, A. Jozwiak, L. Holoidovsky, et al., Glycosylation of N-hydroxy-pipecolic acid equilibrates between systemic acquired resistance response and plant growth, Mol. Plant 14 (2021) 440-455 https://doi.org/10.1016/j.molp.2020.12.018.
|
[2] |
X. Domingo-Almenara, C. Guijas, E. Billings, et al., The METLIN small molecule dataset for machine learning-based retention time prediction, Nat. Commun. 10 (2019) 5811 https://doi.org/10.1038/s41467-019-13680-7.
|
[3] |
J. Xue, C. Guijas, H.P. Benton, et al., METLIN MS(2) molecular standards database: a broad chemical and biological resource, Nat. Methods 17 (2020) 953-954 https://doi.org/10.1038/s41592-020-0942-5.
|
[4] |
J. Shen, L. Jia, L. Dang, et al., StrucGP: de novo structural sequencing of site-specific N-glycan on glycoproteins using a modularization strategy, Nat. Methods 18 (2021) 921-929 https://doi.org/10.1038/s41592-021-01209-0.
|