BASE: a web service for providing compound-protein binding affinity prediction datasets with reduced similarity bias
Abstract Background Deep learning-based drug-target affinity (DTA) prediction methods have shown impressive performance, despite a high number of training parameters relative to the available data. Previous studies have highlighted the presence of dataset bias by suggesting that models trained solel...
Saved in:
| Main Authors: | Hyojin Son, Sechan Lee, Jaeuk Kim, Haangik Park, Myeong-Ha Hwang, Gwan-Su Yi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-10-01
|
| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-024-05968-3 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
FingerDTA: A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction
by: Xuekai Zhu, et al.
Published: (2023-03-01) -
StructureNet: Physics-Informed Hybridized Deep Learning Framework for Protein–Ligand Binding Affinity Prediction
by: Arjun Kaneriya, et al.
Published: (2025-05-01) -
GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity
by: Junwei Luo, et al.
Published: (2025-02-01) -
Binding Affinity Prediction for Pancreatic Ductal Adenocarcinoma Using Drug-Target Descriptors and Artificial Intelligence
by: Pragya, et al.
Published: (2025-01-01) -
Drug-target binding affinity prediction based on power graph and word2vec
by: Jing Hu, et al.
Published: (2025-01-01)