Review on predicting pairwise relationships between human microbes, drugs and diseases: from biological data to computational models
L Wang, Y Tan, X Yang, L Kuang… - Briefings in …, 2022 - academic.oup.com
In recent years, with the rapid development of techniques in bioinformatics and life science,
a considerable quantity of biomedical data has been accumulated, based on which …
a considerable quantity of biomedical data has been accumulated, based on which …
Network approaches for modeling the effect of drugs and diseases
The network approach is quickly becoming a fundamental building block of computational
methods aiming at elucidating the mechanism of action (MoA) and therapeutic effect of …
methods aiming at elucidating the mechanism of action (MoA) and therapeutic effect of …
A geometric deep learning framework for drug repositioning over heterogeneous information networks
Drug repositioning (DR) is a promising strategy to discover new indicators of approved
drugs with artificial intelligence techniques, thus improving traditional drug discovery and …
drugs with artificial intelligence techniques, thus improving traditional drug discovery and …
Prediction of drug-drug interaction events using graph neural networks based feature extraction
MH Al-Rabeah, A Lakizadeh - Scientific Reports, 2022 - nature.com
The prevalence of multi_drug therapies has been increasing in recent years, particularly
among the elderly who are suffering from several diseases. However, unexpected …
among the elderly who are suffering from several diseases. However, unexpected …
[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 …
Prediction of drug pathway-based disease classes using multiple properties of drugs
L Chen, L Li - Current Bioinformatics, 2024 - benthamdirect.com
Background: Drug repositioning now is an important research area in drug discovery as it
can accelerate the procedures of discovering novel effects of existing drugs. However, it is …
can accelerate the procedures of discovering novel effects of existing drugs. However, it is …
A multi-graph deep learning model for predicting drug-disease associations
Computational drug repositioning is essential in drug discovery and development. The
previous methods basically utilized matrix calculation. Although they had certain effects, they …
previous methods basically utilized matrix calculation. Although they had certain effects, they …
Herb-disease association prediction model based on network consistency projection
L Chen, S Zhang, B Zhou - Scientific Reports, 2025 - nature.com
A growing number of biological and clinical reports indicate the usefulness of herbs in the
treatment of complex human diseases, giving an essential supplement for modern medicine …
treatment of complex human diseases, giving an essential supplement for modern medicine …
MNESEDA: A prior-guided subgraph representation learning framework for predicting disease-related enhancers
Enhancers, as a class of functional genomic regulatory elements, activate transcription of
their target genes and play significant roles in the pathogenesis of complex human …
their target genes and play significant roles in the pathogenesis of complex human …
RLFDDA: a meta-path based graph representation learning model for drug–disease association prediction
Background Drug repositioning is a very important task that provides critical information for
exploring the potential efficacy of drugs. Yet developing computational models that can …
exploring the potential efficacy of drugs. Yet developing computational models that can …