[HTML][HTML] Connecting the dots: Computational network analysis for disease insight and drug repurposing
N Siminea, E Czeizler, VB Popescu, I Petre… - Current Opinion in …, 2024 - Elsevier
Highlights•Networks have been successfully applied in biology and medicine for several
decades.•Network methods play a key role in personalized and precision medicine.•Rapid …
decades.•Network methods play a key role in personalized and precision medicine.•Rapid …
SubMDTA: drug target affinity prediction based on substructure extraction and multi-scale features
S Pan, L Xia, L Xu, Z Li - BMC bioinformatics, 2023 - Springer
Background Drug–target affinity (DTA) prediction is a critical step in the field of drug
discovery. In recent years, deep learning-based methods have emerged for DTA prediction …
discovery. In recent years, deep learning-based methods have emerged for DTA prediction …
DrugReAlign: a multisource prompt framework for drug repurposing based on large language models
Drug repurposing is a promising approach in the field of drug discovery owing to its
efficiency and cost-effectiveness. Most current drug repurposing models rely on specific …
efficiency and cost-effectiveness. Most current drug repurposing models rely on specific …
Artificial intelligence accelerates multi-modal biomedical process: A Survey
The abundance of artificial intelligence AI algorithms and growing computing power has
brought a disruptive revolution to the smart medical industry. Its powerful data abstraction …
brought a disruptive revolution to the smart medical industry. Its powerful data abstraction …
NCH-DDA: Neighborhood contrastive learning heterogeneous network for drug–disease association prediction
Exploring new therapeutic diseases for existing drugs plays an essential role in reducing
drug development costs. However, existing methods for predicting drug–disease association …
drug development costs. However, existing methods for predicting drug–disease association …
AMDECDA: attention mechanism combined with data ensemble strategy for predicting CircRNA-disease association
Accumulating evidence from recent research reveals that circRNA is tightly bound to human
complex disease and plays an important regulatory role in disease progression. Identifying …
complex disease and plays an important regulatory role in disease progression. Identifying …
Leveraging pre-trained language models for mining microbiome-disease relationships
N Karkera, S Acharya, SK Palaniappan - BMC bioinformatics, 2023 - Springer
Background The growing recognition of the microbiome's impact on human health and well-
being has prompted extensive research into discovering the links between microbiome …
being has prompted extensive research into discovering the links between microbiome …
Research Progress on Drug-Target Interactions in the Last Five Years
Y Zuo, X Wu, F Ge, H Yan, S Fei, J Liang, Z Deng - Analytical Biochemistry, 2024 - Elsevier
Abstract The identification of Drug-Target Interaction (DTI) is an important step in drug
discovery and drug repositioning, and has high application value in multiple fields such as …
discovery and drug repositioning, and has high application value in multiple fields such as …
[HTML][HTML] AMDGT: Attention aware multi-modal fusion using a dual graph transformer for drug–disease associations prediction
Identification of new indications for existing drugs is crucial through the various stages of
drug discovery. Computational methods are valuable in establishing meaningful …
drug discovery. Computational methods are valuable in establishing meaningful …
Dual-channel hypergraph convolutional network for predicting herb–disease associations
Herbs applicability in disease treatment has been verified through experiences over
thousands of years. The understanding of herb–disease associations (HDAs) is yet far from …
thousands of years. The understanding of herb–disease associations (HDAs) is yet far from …