{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:17:08Z","timestamp":1750220228871,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":39,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,10,26]]},"DOI":"10.1145\/3459637.3482110","type":"proceedings-article","created":{"date-parts":[[2021,10,30]],"date-time":"2021-10-30T18:33:11Z","timestamp":1635618791000},"page":"3323-3327","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["GDFM"],"prefix":"10.1145","author":[{"given":"Sameen","family":"Mansha","sequence":"first","affiliation":[{"name":"Information Technology University of the Punjab, Lahore, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tayyab","family":"Khalid","sequence":"additional","affiliation":[{"name":"Information Technology University of the Punjab, Lahore, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Faisal","family":"Kamiran","sequence":"additional","affiliation":[{"name":"Information Technology University of the Punjab, Lahore, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masroor","family":"Hussain","sequence":"additional","affiliation":[{"name":"Ghulam Ishaq Khan Institute of Engineering, Sciences and Technology, Topi, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Syed Fawad","family":"Hussain","sequence":"additional","affiliation":[{"name":"Ghulam Ishaq Khan Institute of Engineering, Sciences and Technology, Topi, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongzhi","family":"Yin","sequence":"additional","affiliation":[{"name":"The University of Queensland, Brisbane, QLD, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,10,30]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_3_2_1_1_1","DOI":"10.1016\/j.ygeno.2013.07.010"},{"doi-asserted-by":"crossref","unstructured":"Tanya Barrett Dennis B Troup Stephen E Wilhite Pierre Ledoux etal 2010.NCBI GEO: archive for functional genomics data sets-10 years on. Nucleic acids research 39 suppl_1 (2010) D1005--D1010. Tanya Barrett Dennis B Troup Stephen E Wilhite Pierre Ledoux et al. 2010.NCBI GEO: archive for functional genomics data sets-10 years on. Nucleic acids research 39 suppl_1 (2010) D1005--D1010.","key":"e_1_3_2_1_2_1","DOI":"10.1093\/nar\/gkq1184"},{"volume-title":"Biocomputing","year":"2000","author":"Butte Atul J","key":"e_1_3_2_1_3_1"},{"volume-title":"Protein-protein interaction prediction using a hybrid feature representation and a stacked generalization scheme. BMC bioinformatics 20, 1","year":"2019","author":"Chen Kuan-Hsi","key":"e_1_3_2_1_4_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_5_1","DOI":"10.1145\/3269206.3271759"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_6_1","DOI":"10.1109\/ICDE48307.2020.00125"},{"doi-asserted-by":"crossref","unstructured":"Wen Dai Xi Liu Yibo Gao Lin Chen Jianglong Song Di Chen Kuo Gao Yongshi Jiang Yiping Yang etal 2015. Matrix factorization-based prediction of novel drug indications by integrating genomic space. Computational and mathematical methods in medicine (2015). Wen Dai Xi Liu Yibo Gao Lin Chen Jianglong Song Di Chen Kuo Gao Yongshi Jiang Yiping Yang et al. 2015. Matrix factorization-based prediction of novel drug indications by integrating genomic space. Computational and mathematical methods in medicine (2015).","key":"e_1_3_2_1_7_1","DOI":"10.1155\/2015\/275045"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_8_1","DOI":"10.1145\/2939672.2939754"},{"unstructured":"Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li and Xiuqiang He. 2017. DeepFM: a factorization-machine based neural network for CTR prediction. arXiv preprint arXiv:1703.04247 (2017). Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li and Xiuqiang He. 2017. DeepFM: a factorization-machine based neural network for CTR prediction. arXiv preprint arXiv:1703.04247 (2017).","key":"e_1_3_2_1_9_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_10_1","DOI":"10.1145\/3077136.3080777"},{"volume-title":"SkipGNN: predicting molecular interactions with skip-graph networks. Scientific reports 10, 1","year":"2020","author":"Huang Kexin","key":"e_1_3_2_1_11_1"},{"volume-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167","year":"2015","author":"Ioffe Sergey","key":"e_1_3_2_1_12_1"},{"doi-asserted-by":"crossref","unstructured":"K. Kc R. Li F. Cui and A. Haake. 2021. Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks. IEEE\/ACM Transactions on Computational Biology and Bioinformatics (2021) 1--1. K. Kc R. Li F. Cui and A. Haake. 2021. Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks. IEEE\/ACM Transactions on Computational Biology and Bioinformatics (2021) 1--1.","key":"e_1_3_2_1_13_1","DOI":"10.1109\/TCBB.2021.3059415"},{"volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","year":"2016","author":"Kipf Thomas N","key":"e_1_3_2_1_14_1"},{"volume-title":"GNE: a deep learning framework for gene network inference by aggregating biological information. BMC systems biology 13, 2","year":"2019","author":"Kishan KC","key":"e_1_3_2_1_15_1"},{"unstructured":"Ying-Ke Lei Zhu-Hong You Zhen Ji Lin Zhu and De-Shuang Huang. 2012. Assessing and predicting protein interactions by combining manifold embedding with multiple information integration. (2012). Ying-Ke Lei Zhu-Hong You Zhen Ji Lin Zhu and De-Shuang Huang. 2012. Assessing and predicting protein interactions by combining manifold embedding with multiple information integration. (2012).","key":"e_1_3_2_1_16_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_17_1","DOI":"10.1145\/3219819.3220023"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_18_1","DOI":"10.1145\/3354031.3354047"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_19_1","DOI":"10.1109\/ACCESS.2019.2954994"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_20_1","DOI":"10.5555\/3304222.3304251"},{"volume-title":"Prediction of genetic interactions using machine learning and network properties. Frontiers in bioengineering and biotechnology 3","year":"2015","author":"Madhukar Neel S","key":"e_1_3_2_1_21_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_22_1","DOI":"10.1145\/3240323.3240356"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_23_1","DOI":"10.1109\/ICDM.2010.127"},{"volume-title":"A bayesian framework that integrates heterogeneous data for inferring gene regulatory networks. Frontiers in bioengineering and biotechnology 2","year":"2014","author":"Santra Tapesh","key":"e_1_3_2_1_24_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_25_1","DOI":"10.5555\/2627435.2670313"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_26_1","DOI":"10.1093\/nar\/gkj109"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_27_1","DOI":"10.1145\/2736277.2741093"},{"volume-title":"Attention is all you need. arXiv preprint arXiv:1706.03762","year":"2017","author":"Vaswani Ashish","key":"e_1_3_2_1_28_1"},{"volume-title":"Predicting protein-protein interactions from matrix-based protein sequence using convolution neural network and feature-selective rotation forest. Scientific reports 9, 1","year":"2019","author":"Wang Lei","key":"e_1_3_2_1_29_1"},{"doi-asserted-by":"crossref","unstructured":"Jun Xiao Hao Ye Xiangnan He Hanwang Zhang Fei Wu and Tat-Seng Chua. 2017. Attentional factorization machines: Learning the weight of feature interactions via attention networks. (2017). Jun Xiao Hao Ye Xiangnan He Hanwang Zhang Fei Wu and Tat-Seng Chua. 2017. Attentional factorization machines: Learning the weight of feature interactions via attention networks. (2017).","key":"e_1_3_2_1_30_1","DOI":"10.24963\/ijcai.2017\/435"},{"volume-title":"Graph-based prediction of Protein-protein interactions with attributed signed graph embedding. BMC bioinformatics 21, 1","year":"2020","author":"Yang Fang","key":"e_1_3_2_1_31_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_32_1","DOI":"10.1021\/ci500340n"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_33_1","DOI":"10.1016\/j.neucom.2016.10.042"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1093\/bioinformatics\/btz718","article-title":"Graph embedding on biomedical networks: methods, applications and evaluations","volume":"36","author":"Yue Xiang","year":"2020","journal-title":"Bioinformatics"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_35_1","DOI":"10.1016\/j.jbi.2018.11.005"},{"volume-title":"Deep learning over multi-field categorical data","author":"Zhang Weinan","doi-asserted-by":"crossref","key":"e_1_3_2_1_36_1","DOI":"10.1007\/978-3-319-30671-1_4"},{"doi-asserted-by":"crossref","unstructured":"Wen Zhang Xiang Yue Weiran Lin WenjianWu Ruoqi Liu etal 2018. Predicting drug-disease associations by using similarity constrained matrix factorization. BMC bioinformatics 19 1 (2018) 1--12. Wen Zhang Xiang Yue Weiran Lin WenjianWu Ruoqi Liu et al. 2018. Predicting drug-disease associations by using similarity constrained matrix factorization. BMC bioinformatics 19 1 (2018) 1--12.","key":"e_1_3_2_1_37_1","DOI":"10.1186\/s12859-018-2220-4"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_38_1","DOI":"10.1016\/j.neucom.2013.04.027"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_39_1","DOI":"10.1093\/bioinformatics\/bty294"}],"event":{"sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"acronym":"CIKM '21","name":"CIKM '21: The 30th ACM International Conference on Information and Knowledge Management","location":"Virtual Event Queensland Australia"},"container-title":["Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482110","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3459637.3482110","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:12Z","timestamp":1750188612000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482110"}},"subtitle":["Gene Vectors Embodied Deep Attentional Factorization Machines for Interaction prediction"],"short-title":[],"issued":{"date-parts":[[2021,10,26]]},"references-count":39,"alternative-id":["10.1145\/3459637.3482110","10.1145\/3459637"],"URL":"https:\/\/doi.org\/10.1145\/3459637.3482110","relation":{},"subject":[],"published":{"date-parts":[[2021,10,26]]},"assertion":[{"value":"2021-10-30","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}