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Computational approaches are recognized as a valid way to predict bacteria and target phages. However, most of the current methods only utilize lower-order biological information without considering the higher-order connectivity patterns, which helps to improve the predictive accuracy. Therefore, we developed a novel microbial heterogeneous interaction network (MHIN)\u2013based model called PTBGRP to predict new phages for bacterial hosts. Specifically, PTBGRP first constructs an MHIN by integrating phage\u2013bacteria interaction (PBI) and six bacteria\u2013bacteria interaction networks with their biological attributes. Then, different representation learning methods are deployed to extract higher-level biological features and lower-level topological features from MHIN. Finally, PTBGRP employs a deep neural network as the classifier to predict unknown PBI pairs based on the fused biological information. Experiment results demonstrated that PTBGRP achieves the best performance on the corresponding ESKAPE pathogens and PBI dataset when compared with state-of-art methods. In addition, case studies of Klebsiella pneumoniae and Staphylococcus aureus further indicate that the consideration of rich heterogeneous information enables PTBGRP to accurately predict PBI from a more comprehensive perspective. The webserver of the PTBGRP predictor is freely available at http:\/\/120.77.11.78\/PTBGRP\/.<\/jats:p>","DOI":"10.1093\/bib\/bbad328","type":"journal-article","created":{"date-parts":[[2023,9,24]],"date-time":"2023-09-24T03:47:15Z","timestamp":1695527235000},"source":"Crossref","is-referenced-by-count":10,"title":["PTBGRP: predicting phage\u2013bacteria interactions with graph representation learning on microbial heterogeneous information network"],"prefix":"10.1093","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4993-298X","authenticated-orcid":false,"given":"Jie","family":"Pan","sequence":"first","affiliation":[{"name":"Key Laboratory of Resources Biology and Biotechnology in Western China , Ministry of Education, Provincial Key Laboratory of Biotechnology of Shaanxi Province, , Xi\u2019an 710069 , China"},{"name":"the College of Life Sciences, Northwest University , Ministry of Education, Provincial Key Laboratory of Biotechnology of Shaanxi Province, , Xi\u2019an 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