Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors
PN Shiammala, NKB Duraimutharasan, B Vaseeharan… - Methods, 2023 - Elsevier
Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides
opportunities to discover and develop innovative drugs. The use of AI in drug discovery is …
opportunities to discover and develop innovative drugs. The use of AI in drug discovery is …
A comprehensive review of protein-centric predictors for biomolecular interactions: from proteins to nucleic acids and beyond
Proteins interact with diverse ligands to perform a large number of biological functions, such
as gene expression and signal transduction. Accurate identification of these protein–ligand …
as gene expression and signal transduction. Accurate identification of these protein–ligand …
DRGCL: Drug Repositioning via Semantic-enriched Graph Contrastive Learning
Drug repositioning greatly reduces drug development costs and time by discovering new
indications for existing drugs. With the development of technology and large-scale biological …
indications for existing drugs. With the development of technology and large-scale biological …
GraphCL-DTA: a graph contrastive learning with molecular semantics for drug-target binding affinity prediction
X Yang, G Yang, J Chu - IEEE Journal of Biomedical and …, 2024 - ieeexplore.ieee.org
Drug-target binding affinity prediction plays an important role in the early stages of drug
discovery, which can infer the strength of interactions between new drugs and new targets …
discovery, which can infer the strength of interactions between new drugs and new targets …
DualFluidNet: An attention-based dual-pipeline network for fluid simulation
Y Chen, S Zheng, M Jin, Y Chang, N Wang - Neural Networks, 2024 - Elsevier
Fluid motion can be considered as a point cloud transformation when using the SPH
method. Compared to traditional numerical analysis methods, using machine learning …
method. Compared to traditional numerical analysis methods, using machine learning …
Knowledge Graph Convolutional Network with Heuristic Search for Drug Repositioning
Drug repositioning is a strategy of repurposing approved drugs for treating new indications,
which can accelerate the drug discovery process, reduce development costs, and lower the …
which can accelerate the drug discovery process, reduce development costs, and lower the …
A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning
X Zeng, SJ Li, SQ Lv, ML Wen, Y Li - Frontiers in Pharmacology, 2024 - frontiersin.org
Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the
pharmaceutical industry, including drug screening, design, and repurposing. However …
pharmaceutical industry, including drug screening, design, and repurposing. However …
Parallel Multiscale Bridge Fusion Network for Audio-Visual Automatic Depression Assessment
Depression is a prevalent and severe mental illness that significantly impacts patients'
physical health and daily life. Recent studies have focused on multimodal depression …
physical health and daily life. Recent studies have focused on multimodal depression …