Results 111 to 120 of about 5,508,972 (143)

LLMDTA: Improving Cold-Start Prediction in Drug-Target Affinity With Biological LLM

IEEE Transactions on Computational Biology and Bioinformatics
Drug-target affinity (DTA) prediction plays a crucial role in accelerating the drug development process. Although deep learning-based models achieve strong performance in benchmark datasets, their predictive accuracy declines sharply in cold-start ...
Wuguo Tang, Qichang Zhao, Jianxin Wang
semanticscholar   +1 more source

MMSG-DTA: A Multimodal, Multiscale Model Based on Sequence and Graph Modalities for Drug-Target Affinity Prediction

Journal of Chemical Information and Modeling
Drug-Target Affinity (DTA) prediction is a cornerstone of drug discovery and development, providing critical insights into the intricate interactions between candidate drugs and their biological targets.
Jiahao Xu, Ci Lei, Bo Zhu, Guan-Hua Zhang, Linhua Jiang, Shixin Ye-Lehmann, Wei Long   +6 more
semanticscholar   +1 more source

MutualDTA: An Interpretable Drug-Target Affinity Prediction Model Leveraging Pretrained Models and Mutual Attention

Journal of Chemical Information and Modeling
Efficient and accurate drug-target affinity (DTA) prediction can significantly accelerate the drug development process. Recently, deep learning models have been widely applied to DTA prediction and have achieved notable success. However, existing methods
Yong-Na Yuan, Siming Chen, Rizhen Hu, Xin Wang   +3 more
semanticscholar   +1 more source

Drug-Target Affinity Prediction Based on Topological Enhanced Graph Neural Networks

Journal of Chemical Information and Modeling
Graph neural networks (GNNs) have achieved remarkable success in drug-target affinity (DTA) analysis, reducing the cost of drug development. Unlike traditional one-dimensional (1D) sequence-based methods, GNNs leverage graph structures to capture richer ...
Heng-Liang Guo, Cong-Xiang Zhang, Jian-Dong Shang, Du-Juan Zhang, Yang Guo, K. Gao, Kecheng Yang, Xu Gao, De-Zhong Yao, Wanting Chen, Mengfan Yan, Gang Wu   +11 more
semanticscholar   +1 more source

NG-DTA: Drug-target affinity prediction with n-gram molecular graphs

Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2023
Drug–target affinity (DTA) prediction is crucial to speed up drug development. The advance in deep learning allows accurate DTA prediction. However, most deep learning methods treat protein as a 1D string which is not informative to models compared to a ...
Lok-In Tsui, Te-Cheng Hsu, Che Lin
semanticscholar   +1 more source

G-K BertDTA: A graph representation learning and semantic embedding-based framework for drug-target affinity prediction

Comput. Biol. Medicine
Developing new drugs is costly, time-consuming, and risky. Drug-target affinity (DTA), indicating the binding capability between drugs and target proteins, is a crucial indicator for drug development.
Xi-He Qiu, Haoyu Wang, Xiao-Yu Tan, Zhijun Fang   +3 more
semanticscholar   +1 more source

MFF-DTA: Multi-scale Feature Fusion for Drug-Target Affinity Prediction.

Methods
Accurately predicting drug-target affinity is crucial in expediting the discovery and development of new drugs, which is a complex and risky process. Identifying these interactions not only aids in screening potential compounds but also guides further ...
Xiwei Tang, Wanjun Ma, Mengyun Yang, Wen-Jun Li   +3 more
semanticscholar   +1 more source

MHAN-DTA: A Multiscale Hybrid Attention Network for Drug-Target Affinity Prediction

IEEE journal of biomedical and health informatics
Drug-target affinity prediction is a key challenge in the drug discovery process. Recent advances have demonstrated the great potential of deep learning in predicting affinities; however, existing approaches learn the representation of drug-target ...
Jiaren Li, Xiang-Peng Bi, Wen-Jian Ma, Hua-Sen Jiang, Shang-Long Liu, Yun Lu, Zhi-Qiang Wei, Shu-Gang Zhang   +7 more
semanticscholar   +1 more source

Germinal centers output clonally diverse plasma cell populations expressing high- and low-affinity antibodies

Cell, 2023
Colin Bannard, Oliver Bannard
exaly  

Drug-target affinity prediction using rotary encoding and information retention mechanisms

Engineering applications of artificial intelligence
Zhi-Qin Zhu, Yan Ding, Guanqiu Qi, Bai-Sen Cong, Yuanyuan Li, Li-Tao Bai, Xin-Bo Gao   +6 more
semanticscholar   +1 more source