Relation-aware Heterogeneous Graph Transformer based drug repurposing

Graph transformer networks based text representation

(2021) Xin Mei et al.   NEUROCOMPUTING

COVID-19 and Multiorgan Response

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A SARS-CoV-2 protein interaction map reveals targets for drug repurposing

(2020) David E. Gordon et al.   NATURE

DLS: A Link Prediction Method Based on Network Local Structure for Predicting Drug-Protein Interactions

(2020) Wei Wang et al.   Frontiers in Bioengineering and Biotechnology

A library of nucleotide analogues terminate RNA synthesis catalyzed by polymerases of coronaviruses that cause SARS and COVID-19

(2020) Steffen Jockusch et al.   ANTIVIRAL RESEARCH

Toward heterogeneous information fusion: bipartite graph convolutional networks for in silico drug repurposing

(2020) Zichen Wang et al.   BIOINFORMATICS

deepDR: A network-based deep learning approach to in silico drug repositioning

(2019) Xiangxiang Zeng et al.   BIOINFORMATICS

Network-based approach to prediction and population-based validation of in silico drug repurposing

(2018) Feixiong Cheng et al.   Nature Communications

Drug repurposing: progress, challenges and recommendations

(2018) Sudeep Pushpakom et al.   NATURE REVIEWS DRUG DISCOVERY

Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm

(2016) Huimin Luo et al.   BIOINFORMATICS

Network-based in silico drug efficacy screening

(2016) Emre Guney et al.   Nature Communications

Machine learning-based prediction of drug–drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties

(2014) Feixiong Cheng et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

Drug Repositioning: A Machine-Learning Approach through Data Integration

(2013) Francesco Napolitano et al.   Journal of Cheminformatics

PREDICT: a method for inferring novel drug indications with application to personalized medicine

(2011) A. Gottlieb et al.   Molecular Systems Biology

Discovery of drug mode of action and drug repositioning from transcriptional responses

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