A survey of drug-target interaction and affinity prediction methods via graph neural networks
Y Zhang, Y Hu, N Han, A Yang, X Liu, H Cai - Computers in Biology and …, 2023 - Elsevier
The tasks of drug-target interaction (DTI) and drug-target affinity (DTA) prediction play
important roles in the field of drug discovery. However, biological experiment-based …
important roles in the field of drug discovery. However, biological experiment-based …
Revolutionizing adjuvant development: harnessing AI for next-generation cancer vaccines
With the COVID-19 pandemic, the importance of vaccines has been widely recognized and
has led to increased research and development efforts. Vaccines also play a crucial role in …
has led to increased research and development efforts. Vaccines also play a crucial role in …
Variational gated autoencoder-based feature extraction model for inferring disease-miRNA associations based on multiview features
Y Guo, D Zhou, X Ruan, J Cao - Neural Networks, 2023 - Elsevier
MicroRNAs (miRNA) play critical roles in diverse biological processes of diseases. Inferring
potential disease-miRNA associations enable us to better understand the development and …
potential disease-miRNA associations enable us to better understand the development and …
AttentionMGT-DTA: A multi-modal drug-target affinity prediction using graph transformer and attention mechanism
The accurate prediction of drug-target affinity (DTA) is a crucial step in drug discovery and
design. Traditional experiments are very expensive and time-consuming. Recently, deep …
design. Traditional experiments are very expensive and time-consuming. Recently, deep …
REDDA: Integrating multiple biological relations to heterogeneous graph neural network for drug-disease association prediction
Computational drug repositioning is an effective way to find new indications for existing
drugs, thus can accelerate drug development and reduce experimental costs. Recently …
drugs, thus can accelerate drug development and reduce experimental costs. Recently …
Hierarchical graph representation learning for the prediction of drug-target binding affinity
Computationally predicting drug-target binding affinity (DTA) has attracted increasing
attention due to its benefit for accelerating drug discovery. Currently, numerous deep …
attention due to its benefit for accelerating drug discovery. Currently, numerous deep …
The changing scenario of drug discovery using AI to deep learning: Recent advancement, success stories, collaborations, and challenges
Due to the transformation of artificial intelligence (AI) tools and technologies, AI-driven drug
discovery has come to the forefront. It reduces the time and expenditure. Due to these …
discovery has come to the forefront. It reduces the time and expenditure. Due to these …
The changing scenario of drug discovery using artificial intelligence (AI) to deep learning (DL): Recent advancement, success stories, collaborations, and challenges
C Chakraborty, M Bhattacharya, SS Lee… - … Therapy-Nucleic Acids, 2024 - cell.com
Due to the transformation of artificial intelligence (AI) tools and technologies, AI-driven drug
discovery has come to the forefront. It reduces the time and expenditure. Due to these …
discovery has come to the forefront. It reduces the time and expenditure. Due to these …
TransVAE-DTA: Transformer and variational autoencoder network for drug-target binding affinity prediction
C Zhou, Z Li, J Song, W **ang - Computer Methods and Programs in …, 2024 - Elsevier
Background and objective Recent studies have emphasized the significance of
computational in silico drug-target binding affinity (DTA) prediction in the field of drug …
computational in silico drug-target binding affinity (DTA) prediction in the field of drug …
[HTML][HTML] Therapeutic potential of snake venom: Toxin distribution and opportunities in deep learning for novel drug discovery
A Bedraoui, M Suntravat, S El Mejjad, S Enezari… - Medicine in Drug …, 2024 - Elsevier
Snake venom is a rich source of bioactive molecules that hold great promise for therapeutic
applications. These molecules can be broadly classified into enzymes and non-enzymes …
applications. These molecules can be broadly classified into enzymes and non-enzymes …