Cargando…

Multi-type feature fusion based on graph neural network for drug-drug interaction prediction

BACKGROUND: Drug-Drug interactions (DDIs) are a challenging problem in drug research. Drug combination therapy is an effective solution to treat diseases, but it can also cause serious side effects. Therefore, DDIs prediction is critical in pharmacology. Recently, researchers have been using deep le...

Descripción completa

Detalles Bibliográficos
Autores principales:	He, Changxiang, Liu, Yuru, Li, Hao, Zhang, Hui, Mao, Yaping, Qin, Xiaofei, Liu, Lele, Zhang, Xuedian
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2022
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9188183/ https://www.ncbi.nlm.nih.gov/pubmed/35689200 http://dx.doi.org/10.1186/s12859-022-04763-2

Ejemplares similares

Long-distance dependency combined multi-hop graph neural networks for protein–protein interactions prediction
por: Zhong, Wen, et al.
Publicado: (2022)

Detecting Drug–Target Interactions with Feature Similarity Fusion and Molecular Graphs
por: Lin, Xiaoli, et al.
Publicado: (2022)

MSGNN-DTA: Multi-Scale Topological Feature Fusion Based on Graph Neural Networks for Drug–Target Binding Affinity Prediction
por: Wang, Shudong, et al.
Publicado: (2023)

Multi-view feature representation and fusion for drug-drug interactions prediction
por: Wang, Jing, et al.
Publicado: (2023)

An efficient self-attention network for skeleton-based action recognition
por: Qin, Xiaofei, et al.
Publicado: (2022)

Prediction of Drug-Drug Interaction Using an Attention-Based Graph Neural Network on Drug Molecular Graphs
por: Feng, Yue-Hua, et al.
Publicado: (2022)

Prediction of drug-drug interaction events using graph neural networks based feature extraction
por: Al-Rabeah, Mohammad Hussain, et al.
Publicado: (2022)

Multi-Scale Aggregation Graph Neural Networks Based on Feature Similarity for Semi-Supervised Learning
por: Zhang, Xun, et al.
Publicado: (2021)

DDI-MuG: Multi-aspect graphs for drug-drug interaction extraction
por: Yang, Jie, et al.
Publicado: (2023)

RNN-combined graph convolutional network with multi-feature fusion for tuberculosis cavity segmentation
por: Xiao, Zhitao, et al.
Publicado: (2023)

SmileGNN: Drug–Drug Interaction Prediction Based on the SMILES and Graph Neural Network
por: Han, Xueting, et al.
Publicado: (2022)

MDGNN: Microbial Drug Prediction Based on Heterogeneous Multi-Attention Graph Neural Network
por: Pi, Jiangsheng, et al.
Publicado: (2022)

A dual graph neural network for drug–drug interactions prediction based on molecular structure and interactions
por: Ma, Mei, et al.
Publicado: (2023)

MULGA, a unified multi-view graph autoencoder-based approach for identifying drug–protein interaction and drug repositioning
por: Ma, Jiani, et al.
Publicado: (2023)

Drug–disease association prediction with literature based multi-feature fusion
por: Kang, Hongyu, et al.
Publicado: (2023)

Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures
por: Shtar, Guy, et al.
Publicado: (2019)

Nonlinear data fusion over Entity–Relation graphs for Drug–Target Interaction prediction
por: Mazzone, Eugenio, et al.
Publicado: (2023)

An Integrative Heterogeneous Graph Neural Network–Based Method for Multi-Labeled Drug Repurposing
por: Sadeghi, Shaghayegh, et al.
Publicado: (2022)

Multi-Modality Adaptive Feature Fusion Graph Convolutional Network for Skeleton-Based Action Recognition
por: Zhang, Haiping, et al.
Publicado: (2023)

Enhancing drug–drug interaction prediction by three-way decision and knowledge graph embedding
por: Hao, Xinkun, et al.
Publicado: (2022)

RDRGSE: A Framework for Noncoding RNA-Drug Resistance Discovery by Incorporating Graph Skeleton Extraction and Attentional Feature Fusion
por: Zhang, Ping, et al.
Publicado: (2023)

Multi-objective de novo drug design with conditional graph generative model
por: Li, Yibo, et al.
Publicado: (2018)

Drug-Disease Graph: Predicting Adverse Drug Reaction Signals via Graph Neural Network with Clinical Data
por: Kwak, Heeyoung, et al.
Publicado: (2020)

SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization
por: Yu, Yue, et al.
Publicado: (2021)

DeepNC: a framework for drug-target interaction prediction with graph neural networks
por: Tran, Huu Ngoc Tran, et al.
Publicado: (2022)

Multitype drug interaction prediction based on the deep fusion of drug features and topological relationships
por: Kang, Li-Ping, et al.
Publicado: (2022)

A Knowledge-Graph-Based Multimodal Deep Learning Framework for Identifying Drug–Drug Interactions
por: Zhang, Jing, et al.
Publicado: (2023)

Granger-Causality-Based Multi-Frequency Band EEG Graph Feature Extraction and Fusion for Emotion Recognition
por: Zhang, Jing, et al.
Publicado: (2022)

Graph Neural Networks to Advance Anticancer Drug Design
por: Rassil, Asmaa, et al.
Publicado: (2020)

MGRL: Predicting Drug-Disease Associations Based on Multi-Graph Representation Learning
por: Zhao, Bo-Wei, et al.
Publicado: (2021)

DrugRep-HeSiaGraph: when heterogenous siamese neural network meets knowledge graphs for drug repurposing
por: Ghorbanali, Zahra, et al.
Publicado: (2023)

Learning size-adaptive molecular substructures for explainable drug–drug interaction prediction by substructure-aware graph neural network
por: Yang, Ziduo, et al.
Publicado: (2022)

LaGAT: link-aware graph attention network for drug–drug interaction prediction
por: Hong, Yue, et al.
Publicado: (2022)

Convolutional Models with Multi-Feature Fusion for Effective Link Prediction in Knowledge Graph Embedding
por: Guo, Qinglang, et al.
Publicado: (2023)

Drug-target interaction prediction using Multi Graph Regularized Nuclear Norm Minimization
por: Mongia, Aanchal, et al.
Publicado: (2020)

Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network
por: Wang, Shui-Hua, et al.
Publicado: (2021)

ScaffoldGVAE: scaffold generation and hopping of drug molecules via a variational autoencoder based on multi-view graph neural networks
por: Hu, Chao, et al.
Publicado: (2023)

A complete graph-based approach with multi-task learning for predicting synergistic drug combinations
por: Wang, Xiaowen, et al.
Publicado: (2023)

MIFNN: Molecular Information Feature Extraction and Fusion Deep Neural Network for Screening Potential Drugs
por: Wang, Jingjing, et al.
Publicado: (2022)

Systematic Fusion of Multi-Source Cognitive Networks With Graph Learning - A Study on Fronto-Parietal Network
por: Zhang, Xiaofei, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_78nu1hdg8ve8tcl12oco7momrl