Drug–drug interaction prediction: databases, web servers and computational models

Y Zhao, J Yin, L Zhang, Y Zhang… - Briefings in …, 2024 - academic.oup.com
In clinical treatment, two or more drugs (ie drug combination) are simultaneously or
successively used for therapy with the purpose of primarily enhancing the therapeutic …

CODENET: A deep learning model for COVID-19 detection

H Ju, Y Cui, Q Su, L Juan, B Manavalan - Computers in Biology and …, 2024 - Elsevier
Conventional COVID-19 testing methods have some flaws: they are expensive and time-
consuming. Chest X-ray (CXR) diagnostic approaches can alleviate these flaws to some …

[HTML][HTML] Drug-drug interaction extraction from biomedical text using relation BioBERT with BLSTM

M KafiKang, A Hendawi - Machine Learning and Knowledge Extraction, 2023 - mdpi.com
In the context of pharmaceuticals, drug-drug interactions (DDIs) occur when two or more
drugs interact, potentially altering the intended effects of the drugs and resulting in adverse …

MulStack: An ensemble learning prediction model of multilabel mRNA subcellular localization

Z Liu, T Bai, B Liu, L Yu - Computers in Biology and Medicine, 2024 - Elsevier
Subcellular localization of mRNA is related to protein synthesis, cell polarity, cell movement
and other biological regulation mechanisms. The distribution of mRNAs in subcellulars is …

Prediction of Cancer Drug Combinations Based on Multidrug Learning and Cancer Expression Information Injection

S Ren, L Chen, H Hao, L Yu - Future Generation Computer Systems, 2024 - Elsevier
Compared with patients with common diseases, cancer patients usually have a more fragile
cellular microenvironment and more complex or varied complications. Therefore, to meet …

HANSynergy: Heterogeneous Graph Attention Network for Drug Synergy Prediction

N Cheng, L Wang, Y Liu, B Song… - Journal of Chemical …, 2024 - ACS Publications
Drug synergy therapy is a promising strategy for cancer treatment. However, the extensive
variety of available drugs and the time-intensive process of determining effective drug …

[HTML][HTML] SubGE-DDI: A new prediction model for drug-drug interaction established through biomedical texts and drug-pairs knowledge subgraph enhancement

Y Shi, M He, J Chen, F Han, Y Cai - PLOS Computational Biology, 2024 - journals.plos.org
Biomedical texts provide important data for investigating drug-drug interactions (DDIs) in the
field of pharmacovigilance. Although researchers have attempted to investigate DDIs from …

MGDDI: A multi-scale graph neural networks for drug–drug interaction prediction

G Geng, L Wang, Y Xu, T Wang, W Ma, H Duan… - Methods, 2024 - Elsevier
Drug-drug interaction (DDI) prediction is crucial for identifying interactions within drug
combinations, especially adverse effects due to physicochemical incompatibility. While …

A Novel Drug-Drug Interaction Prediction Model Based on Line Subgraph Generation Strategy

T Bai, C Li, X Peng, H Guan, Z Zhang… - … on Bioinformatics and …, 2023 - ieeexplore.ieee.org
Drug-Drug Interaction (DDI) prediction task is helpful for better-understanding drugs. In this
paper, we propose a novel drug-drug interaction prediction model based on line subgraph …