Copyright
©The Author(s) 2022.
World J Clin Cases. Jul 16, 2022; 10(20): 6900-6914
Published online Jul 16, 2022. doi: 10.12998/wjcc.v10.i20.6900
Published online Jul 16, 2022. doi: 10.12998/wjcc.v10.i20.6900
Table 2 Top 10 ingredients based on the network of ingredients
| Rank | Name | Molecule name | Degree |
| 1 | MOL000098 | Quercetin | 97 |
| 2 | MOL000358 | Beta-sitosterol | 42 |
| 3 | MOL002714 | Baicalein | 23 |
| 4 | MOL001792 | DFV (5-deoxyflavanone) | 16 |
| 5 | MOL000449 | Stigmasterol | 13 |
| 6 | MOL002959 | 3’-Methoxydaidzein | 12 |
| 7 | MOL000546 | Diosgenin | 11 |
| 8 | MOL005344 | Ginsenoside rh2 | 10 |
| 9 | MOL004941 | (2R)-7-hydroxy-2-(4-hydroxyphenyl) chroman-4-one | 8 |
| 10 | MOL006331 | 4’,5-Dihydroxyflavone | 7 |
- Citation: Cui XY, Wu X, Lu D, Wang D. Network pharmacology-based strategy for predicting therapy targets of Sanqi and Huangjing in diabetes mellitus. World J Clin Cases 2022; 10(20): 6900-6914
- URL: https://www.wjgnet.com/2307-8960/full/v10/i20/6900.htm
- DOI: https://dx.doi.org/10.12998/wjcc.v10.i20.6900