Results 241 to 250 of about 517,836 (269)

Prediction of drug-target binding affinity based on deep learning models

Computers in Biology and Medicine
The prediction of drug-target binding affinity (DTA) plays an important role in drug discovery. Computerized virtual screening techniques have been used for DTA prediction, greatly reducing the time and economic costs of drug discovery. However, these techniques have not succeeded in reversing the low success rate of new drug development.
Hao, Zhang, Xiaoqian, Liu, Wenya, Cheng, Tianshi, Wang, Yuanyuan, Chen   +4 more
openaire   +2 more sources

ASAP-DTA: Predicting drug-target binding affinity with adaptive structure aware networks

Journal of Bioinformatics and Computational Biology
The prediction of drug-target affinity (DTA) is crucial for efficiently identifying potential targets for drug repurposing, thereby reducing resource wastage. In this paper, we propose a novel graph-based deep learning model for DTA that leverages adaptive structure-aware pooling for graph processing. Our approach integrates a self-attention mechanism
Weibin Ding, Shaohua Jiang, Ting Xu, Zhijian Lyu   +3 more
openaire   +2 more sources

Prediction of drug–target binding affinity based on multi-scale feature fusion

Computers in Biology and Medicine
Accurate prediction of drug-target binding affinity (DTA) plays a pivotal role in drug discovery and repositioning. Although deep learning methods are widely used in DTA prediction, two significant challenges persist: (i) how to effectively represent the complex structural information of proteins and drugs; (ii) how to precisely model the mutual ...
Hui Yu, Wen-Xin Xu, Tian Tan, Zun Liu, Jian-Yu Shi   +4 more
openaire   +2 more sources

Contrastive Meta-Learning for Drug-Target Binding Affinity Prediction

2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022
Mei Li, Sihan Xu, Xiangrui Cai, Zhong Zhang, Hua Ji   +4 more
openaire   +1 more source

TC-DTA: Predicting Drug-Target Binding Affinity With Transformer and Convolutional Neural Networks

IEEE Transactions on NanoBioscience
Bioinformatics is a rapidly evolving field that applies computational methods to analyze and interpret biological data. A key task in bioinformatics is identifying novel drug-target interactions (DTIs), which plays a crucial role in drug discovery.
Xiwei Tang, Yiqiang Zhou, Mengyun Yang, Wenjun Li   +3 more
openaire   +2 more sources

Antibody–drug conjugates: Smart chemotherapy delivery across tumor histologies

Ca-A Cancer Journal for Clinicians, 2022
Paolo Tarantino, Roberto Carmagnani Pestana, Shanu Modi   +2 more
exaly  

Predicting drug–target binding affinity through molecule representation block based on multi-head attention and skip connection

Briefings in Bioinformatics, 2022
Chun-Chun Wang, Xing Chen
exaly  

DTBAPred: Improved Prediction Drug-Target Binding Affinity using Machine Learning Approach

2023 3rd International Conference on Computing and Information Technology (ICCIT), 2023
Mohamed Mamoon Hussein, Saleh Musleh, Hamada R. H. Al-Absi, Muhammad Arif, Tanvir Alam   +4 more
openaire   +1 more source

GPCNDTA: Prediction of drug-target binding affinity through cross-attention networks augmented with graph features and pharmacophores

Computers in Biology and Medicine, 2023
Chun-Chun Wang, Xing Chen
exaly  

GEFA: Early Fusion Approach in Drug-Target Affinity Prediction

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022
TRI MINH NGUYEN, Thin Nguyen, Thao Minh Le   +2 more
exaly