TY - JOUR AU - Denny, J. C. AU - Ritchie, M. D. AU - Basford, M. A. AU - Pulley, J. M. AU - Bastarache, L. AU - Brown-Gentry, K. AU - Wang, D. AU - Masys, D. R. AU - Roden, D. M. AU - Crawford, D. C. PY - 2010 DA - 2010// TI - PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations JO - Bioinformatics VL - 26 UR - https://doi.org/10.1093/bioinformatics/btq126 DO - 10.1093/bioinformatics/btq126 ID - Denny2010 ER - TY - JOUR AU - Özgür, A. AU - Vu, T. AU - Erkan, G. AU - Radev, D. R. PY - 2008 DA - 2008// TI - Identifying gene-disease associations using centrality on a literature mined gene-interaction network JO - Bioinformatics VL - 24 UR - https://doi.org/10.1093/bioinformatics/btn182 DO - 10.1093/bioinformatics/btn182 ID - Özgür2008 ER - TY - JOUR AU - Nikdelfaz, O. AU - Jalili, S. PY - 2018 DA - 2018// TI - Disease genes prediction by HMM based PU-learning using gene expression profiles JO - J Biomed Inform VL - 81 UR - https://doi.org/10.1016/j.jbi.2018.03.006 DO - 10.1016/j.jbi.2018.03.006 ID - Nikdelfaz2018 ER - TY - JOUR AU - Vasighizaker, A. AU - Jalili, S. PY - 2018 DA - 2018// TI - C-PUGP: A cluster-based positive unlabeled learning method for disease gene prediction and prioritization JO - Comput Biol Chem VL - 76 UR - https://doi.org/10.1016/j.compbiolchem.2018.05.022 DO - 10.1016/j.compbiolchem.2018.05.022 ID - Vasighizaker2018 ER - TY - JOUR AU - Yue, X. AU - Wang, Z. AU - Huang, J. AU - Parthasarathy, S. AU - Moosavinasab, S. AU - Huang, Y. AU - Lin, S. M. AU - Zhang, W. AU - Zhang, P. AU - Sun, H. PY - 2019 DA - 2019// TI - Graph embedding on biomedical networks: methods, applications and evaluations JO - Bioinformatics VL - 36 ID - Yue2019 ER - TY - JOUR AU - Li, Y. AU - Patra, J. C. PY - 2010 DA - 2010// TI - Genome-wide inferring gene–phenotype relationship by walking on the heterogeneous network JO - Bioinformatics VL - 26 UR - https://doi.org/10.1093/bioinformatics/btq108 DO - 10.1093/bioinformatics/btq108 ID - Li2010 ER - TY - JOUR AU - Wang, X. AU - Gulbahce, N. AU - Yu, H. PY - 2011 DA - 2011// TI - Network-based methods for human disease gene prediction JO - Brief Funct Genom VL - 10 UR - https://doi.org/10.1093/bfgp/elr024 DO - 10.1093/bfgp/elr024 ID - Wang2011 ER - TY - JOUR AU - Yang, K. AU - Wang, R. AU - Liu, G. AU - Shu, Z. AU - Wang, N. AU - Zhang, R. AU - Yu, J. AU - Chen, J. AU - Li, X. AU - Zhou, X. PY - 2018 DA - 2018// TI - HerGePred: heterogeneous network embedding representation for disease gene prediction JO - IEEE J Biomed Health Inform VL - 23 UR - https://doi.org/10.1109/JBHI.2018.2870728 DO - 10.1109/JBHI.2018.2870728 ID - Yang2018 ER - TY - STD TI - Han P, Yang P, Zhao P, Shang S, Liu Y, Zhou J, Gao X, Kalnis P. GCN-MF: disease-gene association identification by graph convolutional networks and matrix factorization. In: Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining, Anchorage, AK, USA. Association for Computing Machinery. 2019. p. 705–13. ID - ref9 ER - TY - STD TI - Grover A, Leskovec J. node2vec: scalable feature learning for networks. In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, San Francisco, California, USA. Association for Computing Machinery. 2016. p. 855–64. ID - ref10 ER - TY - STD TI - Perozzi B, Al-Rfou R, Skiena S. DeepWalk: online learning of social representations. In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining, New York, New York, USA. Association for Computing Machinery. 2014. p. 701–10. ID - ref11 ER - TY - STD TI - Tang J, Qu M, Wang M, Zhang M, Yan J, Mei Q. LINE: large-scale Information Network Embedding. In: Proceedings of the 24th international conference on world wide web, Florence, Italy. International World Wide Web Conferences Steering Committee. 2015. p. 1067–1077. ID - ref12 ER - TY - STD TI - Dong Y, Chawla NV, Swami A. metapath2vec: scalable representation learning for heterogeneous networks. In: Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining, Halifax, NS, Canada. Association for Computing Machinery. 2017. p. 135–144. ID - ref13 ER - TY - STD TI - Wang X, Ji H, Shi C, Wang B, Ye Y, Cui P, Yu PS. Heterogeneous graph attention network. In: The world wide web conference, San Francisco, CA, USA. Association for Computing Machinery. 2019. p. 2022–32. ID - ref14 ER - TY - STD TI - Veličković P, Cucurull G, Casanova A, Romero A, Lio P, Bengio Y. Graph attention networks. arXiv preprint arXiv:171010903 (2017). UR - http://arxiv.org/abs/171010903 ID - ref15 ER - TY - STD TI - Qu Y, Bai T, Zhang W, Nie J, Tang J. An end-to-end neighborhood-based interaction model for knowledge-enhanced recommendation. In: Proceedings of the 1st international workshop on deep learning practice for high-dimensional sparse data, Anchorage, Alaska. Association for Computing Machinery. 2019: Article 8. ID - ref16 ER - TY - STD TI - Yang Y, Feng Z, Song M, Wang X. Factorizable graph convolutional networks. arXiv preprint arXiv:201005421 (2020). UR - http://arxiv.org/abs/201005421 ID - ref17 ER - TY - STD TI - Fu T-Y, Lee W-C, Lei Z. HIN2Vec: explore meta-paths in heterogeneous information networks for representation learning. In: Proceedings of the 2017 ACM on conference on information and knowledge management, Singapore, Singapore. Association for Computing Machinery. 2017. p. 1797–806. ID - ref18 ER - TY - JOUR AU - Shi, C. AU - Hu, B. AU - Zhao, W. X. AU - Philip, S. Y. PY - 2018 DA - 2018// TI - Heterogeneous information network embedding for recommendation JO - IEEE Trans Knowl Data Eng VL - 31 UR - https://doi.org/10.1109/TKDE.2018.2833443 DO - 10.1109/TKDE.2018.2833443 ID - Shi2018 ER - TY - STD TI - Fu X, Zhang J, Meng Z, King I. MAGNN: metapath aggregated graph neural network for heterogeneous graph embedding. In: Proceedings of the web conference 2020, Taipei, Taiwan. Association for Computing Machinery. 2020. p. 2331–2341. ID - ref20 ER - TY - STD TI - Mikolov T, Sutskever I, Chen K, Corrado G, Dean J. Distributed representations of words and phrases and their compositionality. In: Proceedings of the 26th international conference on neural information processing systems, vol 2, Lake Tahoe, Nevada. Curran Associates Inc. 2013. p. 3111–9. ID - ref21 ER -