Research on the optimization model of anti-breast cancer candidate drugs based on machine learning
Breast cancer is one of the most common malignancies among women globally, with its incidence rate continuously increasing, posing a serious threat to women’s health. Although current treatments, such as drugs targeting estrogen receptor alpha (ERα), have extended patient survival, issues such as dr...
Saved in:
| Main Authors: | Zhou Dong, Hong Chen, Yuchen Yang, Hairong Hao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-04-01
|
| Series: | Frontiers in Genetics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2025.1523015/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
QSAR of acyl alizarin red biocompound derivatives of <i>Rubia tinctorum</i> roots and its ADMET properties as anti-breast cancer candidates against MMP-9 protein receptor: <i>In Silico</i> study
by: M. R.T. Alifiansyah, et al.
Published: (2024-07-01) -
Activity Prediction of Various Herbicides against Honey Bee, Avian, and Multiple Human Leukemia, CNS, Ovarian, Prostate Cancer Cell Lines
by: Kafa Khalaf Hammud
Published: (2023-06-01) -
Substituted 1,4-naphthoquinones for potential anticancer therapeutics: In vitro cytotoxic effects and QSAR-guided design of new analogs
by: Veda Prachayasittikul, et al.
Published: (2025-01-01) -
Rapid discovery of Transglutaminase 2 inhibitors for celiac disease with boosting ensemble machine learning
by: Ibrahim Wichka, et al.
Published: (2024-12-01) -
In silico design of novel dihydropteridone derivatives with oxadiazoles as potent inhibitors of MCF-7 breast cancer cells
by: Mourad Aloui, et al.
Published: (2025-07-01)