Fundamentals of protein interaction network mapping
Studying protein interaction networks of all proteins in an organism (“interactomes”) remains
one of the major challenges in modern biomedicine. Such information is crucial to …
one of the major challenges in modern biomedicine. Such information is crucial to …
Application of Artificial Intelligence in Drug–Drug Interactions Prediction: A Review
Y Zhang, Z Deng, X Xu, Y Feng… - Journal of chemical …, 2023 - ACS Publications
Drug–drug interactions (DDI) are a critical aspect of drug research that can have adverse
effects on patients and can lead to serious consequences. Predicting these events …
effects on patients and can lead to serious consequences. Predicting these events …
Deep learning improves prediction of drug–drug and drug–food interactions
Drug interactions, including drug–drug interactions (DDIs) and drug–food constituent
interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug …
interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug …
Multi-view graph contrastive representation learning for drug-drug interaction prediction
Potential Drug-Drug Interactions (DDI) occur while treating complex or co-existing diseases
with drug combinations, which may cause changes in drugs' pharmacological activity …
with drug combinations, which may cause changes in drugs' pharmacological activity …
MDF-SA-DDI: predicting drug–drug interaction events based on multi-source drug fusion, multi-source feature fusion and transformer self-attention mechanism
One of the main problems with the joint use of multiple drugs is that it may cause adverse
drug interactions and side effects that damage the body. Therefore, it is important to predict …
drug interactions and side effects that damage the body. Therefore, it is important to predict …
Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data
Abstract Background Drug-drug interactions (DDIs) are one of the major concerns in drug
discovery. Accurate prediction of potential DDIs can help to reduce unexpected interactions …
discovery. Accurate prediction of potential DDIs can help to reduce unexpected interactions …
Machine learning-based prediction of drug–drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties
Abstract Objective Drug–drug interactions (DDIs) are an important consideration in both
drug development and clinical application, especially for co-administered medications …
drug development and clinical application, especially for co-administered medications …
A comprehensive review of computational methods for drug-drug interaction detection
The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance,
which provides effective and safe co-prescriptions of multiple drugs. Since laboratory …
which provides effective and safe co-prescriptions of multiple drugs. Since laboratory …
Novel deep learning model for more accurate prediction of drug-drug interaction effects
G Lee, C Park, J Ahn - BMC bioinformatics, 2019 - Springer
Background Predicting the effect of drug-drug interactions (DDIs) precisely is important for
safer and more effective drug co-prescription. Many computational approaches to predict the …
safer and more effective drug co-prescription. Many computational approaches to predict the …
[HTML][HTML] Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives
Highlights•Review of the state-of-the-art in the field of compound combination modelling.•
Significance of quality control of large-scale combination screening data.•Strategies for …
Significance of quality control of large-scale combination screening data.•Strategies for …