miRDDCR: a miRNA-based method to comprehensively infer drug-disease causal relationships
Sign Up to like & getrecommendations! Published in 2017 at "Scientific Reports"
DOI: 10.1038/s41598-017-15716-8
Abstract: Revealing the cause-and-effect mechanism behind drug-disease relationships remains a challenging task. Recent studies suggested that drugs can target microRNAs (miRNAs) and alter their expression levels. In the meanwhile, the inappropriate expression of miRNAs will lead… read more here.
Keywords: disease; drug; drug disease; disease causal ... See more keywords
Predicting drug-disease associations with heterogeneous network embedding.
Sign Up to like & getrecommendations! Published in 2019 at "Chaos"
DOI: 10.1063/1.5121900
Abstract: The prediction of drug-disease associations holds great potential for precision medicine in the era of big data and is important for the identification of new indications for existing drugs. The associations between drugs and diseases… read more here.
Keywords: drug; heterogeneous network; disease associations; drug disease ... See more keywords
A weighted bilinear neural collaborative filtering approach for drug repositioning
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbab581
Abstract: Drug repositioning is an efficient and promising strategy for traditional drug discovery and development. Many research efforts are focused on utilizing deep-learning approaches based on a heterogeneous network for modeling complex drug-disease associations. Similar to… read more here.
Keywords: drug repositioning; disease; drug disease; disease associations ... See more keywords
Learning multi-scale heterogenous network topologies and various pairwise attributes for drug-disease association prediction
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac009
Abstract: MOTIVATION Identifying new therapeutic effects for the approved drugs is beneficial for effectively reducing the drug development cost and time. Most of the recent computational methods concentrate on exploiting multiple kinds of information about drugs… read more here.
Keywords: multi scale; drug; prediction; drug disease ... See more keywords
Similarity measures based graph co-contrastive learning for drug-disease association prediction.
Sign Up to like & getrecommendations! Published in 2023 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btad357
Abstract: MOTIVATION An imperative step in drug discovery is the prediction of drug-disease associations (DDAs), which tries to uncover potential therapeutic possibilities for already validated drugs. It is costly and time-consuming to predict DDAs using wet… read more here.
Keywords: graph contrastive; drug disease; prediction; contrastive learning ... See more keywords
Drug repositioning through integration of prior knowledge and projections of drugs and diseases
Sign Up to like & getrecommendations! Published in 2019 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btz182
Abstract: MOTIVATION Identifying and developing novel therapeutic effects for existing drugs contributes to reduction of drug development costs. Most of the previous methods focus on integration of the heterogeneous data of drugs and diseases frommultiple sources… read more here.
Keywords: drug; prior knowledge; drug disease; drugs diseases ... See more keywords
Successful deployment of drug-disease interaction clinical decision support across multiple Kaiser Permanente regions
Sign Up to like & getrecommendations! Published in 2019 at "Journal of the American Medical Informatics Association : JAMIA"
DOI: 10.1093/jamia/ocz020
Abstract: OBJECTIVE The study sought to develop a criteria-based scoring tool for assessing drug-disease knowledge base content and creation of a subset and to implement the subset across multiple Kaiser Permanente (KP) regions. MATERIALS AND METHODS… read more here.
Keywords: across multiple; disease; multiple kaiser; drug disease ... See more keywords
Prediction of Drug-Disease Associations for Drug Repositioning Through Drug-miRNA-Disease Heterogeneous Network
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2860632
Abstract: Drug repositioning, which refers to the identification of new clinical indications for existing drugs, has become an important strategy for drug discovery. The most recent studies in pharmacogenomics have demonstrated that drugs can target microRNAs… read more here.
Keywords: drug repositioning; drug mirna; disease associations; disease ... See more keywords
Partner-Specific Drug Repositioning Approach Based on Graph Convolutional Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3194891
Abstract: Drug repositioning identifies novel therapeutic potentials for existing drugs and is considered an attractive approach due to the opportunity for reduced development timelines and overall costs. Prior computational methods usually learned a drug's representation from… read more here.
Keywords: graph convolutional; drug disease; drug; partner specific ... See more keywords
NetPro: Neighborhood Interaction-based Drug Repositioning via Label Propagation.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2023.3234331
Abstract: Drug repositioning is an important approach for predicting new disease indications of the existing drugs in drug discovery. A great progress has been achieved in drug repositioning. However, effectively utilizing the localized neighborhood interaction features… read more here.
Keywords: drug repositioning; neighborhood interaction; disease; drug disease ... See more keywords
A drug‐disease model for predicting survival in an Ebola outbreak
Sign Up to like & getrecommendations! Published in 2022 at "Clinical and Translational Science"
DOI: 10.1111/cts.13383
Abstract: REGN‐EB3 (Inmazeb) is a cocktail of three human monoclonal antibodies approved for treatment of Ebola infection. This paper describes development of a mathematical model linking REGN‐EB3’s inhibition of Ebola virus to survival in a non‐human… read more here.
Keywords: time; disease; regn eb3; survival ... See more keywords