2023年9月9日 · Therefore, we propose a learning-based framework named BG-DTI for drug–target interaction prediction. Our model combines two main approaches based on biological features and heterogeneous networks to identify interactions between drugs and targets. First, we extract original features from the sequence to encode each drug and target.

BG-DTI: A biological feature and heterogeneous network representation learning-based framework for drug–target interaction prediction. ###Citation： If you have used BG-DTI or its modules in your research, please cite this paper

2023年9月9日 · Therefore, we propose a learning-based framework named BG-DTI for drug-target interaction prediction. Our model combines two main approaches based on biological features and heterogeneous networks to identify interactions between drugs and targets. First, we extract original features from the sequence to encode each drug and target.

BG-DTI: A biological feature and heterogeneous network representation learning-based framework for drug–target interaction prediction. ###Citation： If you have used BG-DTI or its modules in your research, please cite this paper

2023年9月9日 · Therefore, we propose a learning-based framework named BG-DTI for drug–target interaction prediction. Our model combines two main approaches based on biological features and heterogeneous...

2023年9月1日 · A learning-based framework named BG-DTI for drug–target interaction prediction which combines two main approaches based on biological features and heterogeneous networks to identify interactions between drugs and targets and can facilitate the development of drug discovery or drug repurposing.

2024年8月12日 · 我们量化了三种mri指标：基底节血管周围间隙（bg-pvs）体积、fw分数和dti-alps。 我们使用潜在变化分数模型来检验这3种MRI指标之间的相互关系，并使用线性回归混合模型来检验它们与其他SVD MRI标记物变化和认知表现的纵向关联。

Although the interactions between the drug and target can be accurately verified by traditional biochemical experiments, the determination of DTI through biochemical experiments is a time-consuming, laborious, and expensive process. Therefore, we propose a learning-based framework named BG-DTI for drug-target interaction prediction.

A biological feature and heterogeneous network representation learning-based framework for drug–target interaction prediction - wyx2012/BG-DTI

2021年9月2日 · Given a heterogeneous network containing multiple types of biological entities (i.e. drug, protein, disease, side-effect), EEG-DTI learns the low-dimensional feature representation of drugs and targets using a graph convolutional networks-based model and predicts DTIs based on the learned features.