1.1 DDI prediction 1.2 Drug-drug graph 二、相关研究 三、Method :DSN-DDI 3.1 Overview 3.2 Drug representation learning 3.3 DSN decoder 3.4 Objective function 3.5 Datasets 3.6 Baselines 论文链接:academic.oup.com/bib/ar 代码链接:github.com/microsoft/Dr 关键词:drug-drug interaction, 图神经网络GNN 一...
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics) bioinformaticsdeep-learningtoolkitddidrug-discoverydrug-repurposingppiprotein-protein-interactionside-effectsqsarvirtual-screeningprotein-function-predictiondrug-drug-interactiondrug-target-interactionscovid19drug...
Drug-Drug Interaction Prediction by Neural Network Using Integrated Similarity Due to the great importance of this issue in the economy, industry, and health, proposing appropriate computational methods for predicting unknown DDI with high precision is challenging. We propose a novel machine learning met...
基于局部子结构特征及其互补的药物相互作用预测Drug–drug interaction prediction based on local substructure features and their complements.docxDrug–drug interaction prediction based on local substruc…
Besides, how to fully incorporate the known interaction relationships to accurately represent drugs and targets is not well investigated. Therefore, there is still a need to improve the accuracy of DTI prediction models. RESULTS. In this study, we propose a novel approach that employs Multi-view ...
Prediction of drug-target interactions (DTI) plays a vital role in drug development in various areas, such as virtual screening, drug repurposing and identification of potential drug side effects. Despite extensive efforts have been invested in perfectin
We adopt three representative methods: the neighbor recommender method, the random walk method and the matrix perturbation method to build prediction models based on different data. Thus, we evaluate the usefulness of different information sources for the DDI prediction. Further, we present flexible ...
All data used in this paper are publicly available and can be accessed at http://dude.docking.org for the DUD-E dataset, https://github.com/IBMInterpretableDTIP for the BindingDB-IBM dataset, https://github.com/masashitsubaki/CPI_prediction/tree/master/dataset for human dataset and https:...
We used 3D molecular graph structure and position information to enhance the prediction ability of the model for DDI, which enabled us to deeply explore the effect of drug substructure on DDI relationship. The results showed that 3DGT-DDI outperforms other state-of-the-art baselines. It ...
This is the code repo with model and materials for the corresponding work:Drug-Drug Interaction Prediction on a Biomedical Literature Knowledge Graphpresented inAIME2020. Our model is based on extracting the semantic paths that connect two drug nodes in a KG. The KG is disease-specific and based...