Deep mining heterogeneous networks of biomedical linked data to predict novel drug‐target associations

166 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep learning in bioinformatics: introduction, application, and perspective in big data era (2019, background): “Graph convolutional neural networks (GCN), shown in Fig.”
Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities (2018, background): “Furthermore, the number of associated compounds for each gene is highly uneven [19], with many uncharacter-”
Machine learning approaches and databases for prediction of drug–target interaction: a survey paper (2020, methodology): “[118] DeepDTIs DrugBank Luo et al. [197] DTINet DrugBank, HPRD Zong et al. [117] DeepWalk DrugBank He et al. [159] SimBoost, SimBoostQuant The trend of using such continuous-valued datasets may eventually catch on as it is more useful and more meaningful, in the sense that it represents the reality…”