Predicting drug-disease associations with heterogeneous network embedding.
暂无分享,去创建一个
[1] Juan Wang,et al. The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method , 2018, BMC Bioinformatics.
[2] R. Tagliaferri,et al. Discovery of drug mode of action and drug repositioning from transcriptional responses , 2010, Proceedings of the National Academy of Sciences.
[3] Xiangxiang Zeng,et al. Prediction of Drug–Gene Interaction by Using Metapath2vec , 2018, Front. Genet..
[4] Anaïs Baudot,et al. Random Walk With Restart on Multiplex and Heterogeneous Biological Networks , 2017, bioRxiv.
[5] Yi Pan,et al. Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm , 2016, Bioinform..
[6] Jian Pei,et al. A Survey on Network Embedding , 2017, IEEE Transactions on Knowledge and Data Engineering.
[7] R. Sharan,et al. PREDICT: a method for inferring novel drug indications with application to personalized medicine , 2011, Molecular systems biology.
[8] Chuang Liu,et al. Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference , 2012, PLoS Comput. Biol..
[9] Jian Peng,et al. A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information , 2017, Nature Communications.
[10] Johan A. K. Suykens,et al. Optimal control by least squares support vector machines , 2001, Neural Networks.
[11] Thomas C. Wiegers,et al. The Comparative Toxicogenomics Database: update 2019 , 2018, Nucleic Acids Res..
[12] Leo Katz,et al. A new status index derived from sociometric analysis , 1953 .
[13] David S. Wishart,et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets , 2007, Nucleic Acids Res..
[14] John O. Woods,et al. Prediction and Validation of Gene-Disease Associations Using Methods Inspired by Social Network Analyses , 2013, PloS one.
[15] Jagdish Chandra Patra,et al. Genome-wide inferring gene-phenotype relationship by walking on the heterogeneous network , 2010, Bioinform..
[16] Natalia Novac,et al. Challenges and opportunities of drug repositioning. , 2013, Trends in pharmacological sciences.
[17] Zuping Zhang,et al. Prediction of Drug-Disease Associations for Drug Repositioning Through Drug-miRNA-Disease Heterogeneous Network , 2018, IEEE Access.
[18] T. Ashburn,et al. Drug repositioning: identifying and developing new uses for existing drugs , 2004, Nature Reviews Drug Discovery.
[19] Hojung Nam,et al. Drug repositioning of herbal compounds via a machine-learning approach , 2019, BMC Bioinformatics.
[20] Feng Liu,et al. Predicting drug-disease associations by using similarity constrained matrix factorization , 2018, BMC Bioinformatics.
[21] P. Jaccard,et al. Etude comparative de la distribution florale dans une portion des Alpes et des Jura , 1901 .
[22] Hsiang-Yuan Yeh,et al. Inferring drug-disease associations from integration of chemical, genomic and phenotype data using network propagation , 2013, BMC Medical Genomics.
[23] Armando Blanco,et al. DrugNet: Network-based drug-disease prioritization by integrating heterogeneous data , 2015, Artif. Intell. Medicine.
[24] Hao Ye,et al. Construction of Drug Network Based on Side Effects and Its Application for Drug Repositioning , 2014, PloS one.
[25] Xiang Zhang,et al. Drug repositioning by integrating target information through a heterogeneous network model , 2014, Bioinform..