Results 91 to 100 of about 5,508,972 (143)

MFAE: Multilevel Feature Aggregation Enhanced Drug‐Target Affinity Prediction for Drug Repurposing Against Colorectal Cancer

Advanced Intelligent Systems
Colorectal cancer (CRC), a leading cause of cancer‐related deaths globally, demands innovative therapeutic strategies to improve patient outcomes. Drug repurposing, identifying new uses for existing drugs, provides a cost‐effective solution. To this end,
Guanxing Chen, Haohuai He, Calvin Yu-Chian Chen   +2 more
doaj   +1 more source

GramSeq-DTA: A Grammar-Based Drug–Target Affinity Prediction Approach Fusing Gene Expression Information

Biomolecules
Drug–target affinity (DTA) prediction is a critical aspect of drug discovery. The meaningful representation of drugs and targets is crucial for accurate prediction. Using 1D string-based representations for drugs and targets is a common approach that has
Kusal Debnath, Pratip Rana, Preetam Ghosh   +2 more
doaj   +1 more source

Evaluation of the Peer Support Program (Student Drug Prevention) 1986-1987

, 2019
The Peer Support program is a school based program funded by the National Campaign Against Drug Abuse (NCADA) as a drug prevention strategy. Prior to the existence of the NCADA the program was funded through the NSW Drug and Alcohol Authority.
Directorate of the Drug Offensive
core   +1 more source

A meta learning and task adaptive approach for drug target affinity prediction

Nature Communications
Accurate and robust prediction of drug-target affinity (DTA) plays a critical role in drug discovery. While deep learning has advanced DTA prediction, existing methods struggle with limited training data and poor generalization. In this study, we propose
Mengxuan Wan, Yanpeng Zhao, Yixin Zhang, Huiyan Xu, Duoyun Yi, Peng Zan, Song He, Xiaochen Bo   +7 more
doaj   +1 more source

DynHeter-DTA: Dynamic Heterogeneous Graph Representation for Drug-Target Binding Affinity Prediction

In drug development, drug-target affinity (DTA) prediction is a key indicator for assessing the drug’s efficacy and safety. Despite significant progress in deep learning-based affinity prediction approaches in recent years, there are still ...
Changli Li, Guangyue Li
core   +1 more source

KAN-GIN: Adaptive Nonlinear Molecular Representation Learning for Drug-Target Affinity Prediction

Pharmaceuticals
Background/Objectives: Accurate drug-target affinity (DTA) prediction supports virtual screening, lead optimization, and drug repurposing. This study investigates whether replacing the conventional post-aggregation multilayer perceptron within a Graph ...
Abla Bedoui, Nithyadevi Duraisamy, Mohammed Cherkaoui   +2 more
doaj   +1 more source

SMFF-DTA: using a sequential multi-feature fusion method with multiple attention mechanisms to predict drug-target binding affinity

BMC Biology
Background Drug-target binding affinity (DTA) prediction can accelerate the drug screening process, and deep learning techniques have been used in all facets of drug research.
Xun Wang, Zhijun Xia, Runqiu Feng, Tongyu Han, Hanyu Wang, Wenqian Yu, Xingguang Wang   +6 more
doaj   +1 more source

Adaptive Self-Attention Graph Pooling for Drug–Target Affinity Prediction

International Journal of Molecular Sciences
Drug–target affinity (DTA) prediction is a critical step in drug discovery and precision medicine. Although graph neural networks (GNNs) have achieved remarkable progress, existing graph pooling methods rely on fixed ratios, failing to adapt to the ...
Changli Li, Guangyue Li
semanticscholar   +1 more source

GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity

BMC Genomics
Background Drug-target binding affinity (DTA) prediction is vital in drug discovery and repositioning, more and more researchers are beginning to focus on this. Many effective methods have been proposed.
Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen   +5 more
doaj   +1 more source

A geometric graph-based deep learning model for drug-target affinity prediction

BMC Bioinformatics
In structure-based drug design, accurately estimating the binding affinity between a candidate ligand and its protein receptor is a central challenge.
Md Masud Rana, Farjana Tasnim Mukta, Duc D. Nguyen   +2 more
doaj   +1 more source