QSAR modeling of aromatase inhibition by flavonoids using machine learning approaches
Aromatase is a member of the cytochrome P450 family responsible for catalyzing the rate-limiting conversion of androgens to estrogens. In the pursuit of robust aromatase inhibitors, quantitative structure-activity relationship (QSAR) and classification structure-activity relationship (CSAR) studies...
Saved in:
Main Authors: | Chanin Nantasenamat, Apilak Worachartcheewan, Prasit Mandi, Teerawat Monnor, Chartchalerm Isarankura-Na-Ayudhya, Virapong Prachayasittikul |
---|---|
Other Authors: | Mahidol University |
Format: | Article |
Published: |
2018
|
Subjects: | |
Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/33334 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Mahidol University |
Similar Items
-
Exploring the chemical space of aromatase inhibitors
by: Chanin Nantasenamat, et al.
Published: (2018) -
Predictive QSAR modeling of aldose reductase inhibitors using Monte Carlo feature selection
by: Chanin Nantasenamat, et al.
Published: (2018) -
QSAR modeling of aromatase inhibitory activity of 1-substituted 1,2,3-triazole analogs of letrozole
by: Chanin Nantasenamat, et al.
Published: (2018) -
Large-scale QSAR study of aromatase inhibitors using SMILES-based descriptors
by: Apilak Worachartcheewan, et al.
Published: (2018) -
QSAR study of amidino bis-benzimidazole derivatives as potent anti-malarial agents against Plasmodium falciparum
by: Apilak Worachartcheewan, et al.
Published: (2018)