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Recently, computational tools have been introduced to predict the harmfulness of synonymous mutations. However, most of these computational tools rely on balanced training sets without considering abundant negative samples that could result in deficient performance. In this study, we propose a computational model that uses a selective ensemble to predict deleterious synonymous mutations (seDSM). We construct several candidate base classifiers for the ensemble using balanced training subsets randomly sampled from the imbalanced benchmark training sets. The diversity measures of the base classifiers are calculated by the pairwise diversity metrics, and the classifiers with the highest diversities are selected for integration using soft voting for synonymous mutation prediction. We also design two strategies for filling in missing values in the imbalanced dataset and constructing models using different pairwise diversity metrics. The experimental results show that a selective ensemble based on double fault with the ensemble strategy EKNNI for filling in missing values is the most effective scheme. Finally, using 40-dimensional biology features, we propose a novel model based on a selective ensemble for predicting deleterious synonymous mutations (seDSM). seDSM outperformed other state-of-the-art methods on the independent test sets according to multiple evaluation indicators, indicating that it has an outstanding predictive performance for deleterious synonymous mutations. We hope that seDSM will be useful for studying deleterious synonymous mutations and advancing our understanding of synonymous mutations. The source code of seDSM is freely accessible at https:\/\/github.com\/xialab-ahu\/seDSM.git.<\/jats:p>","DOI":"10.1093\/bib\/bbac598","type":"journal-article","created":{"date-parts":[[2023,1,8]],"date-time":"2023-01-08T04:42:57Z","timestamp":1673152977000},"source":"Crossref","is-referenced-by-count":4,"title":["Deleterious synonymous mutation identification based on selective ensemble strategy"],"prefix":"10.1093","volume":"24","author":[{"given":"Lihua","family":"Wang","sequence":"first","affiliation":[{"name":"GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, State Key Laboratory of Respiratory Disease, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People\u2019s Hospital, Guangzhou Medical University , Guangzhou, Guangdong 511436 , China"},{"name":"Institutes of Physical Science and Information Technology and School of Computer Science and Technology, Anhui University , Hefei, Anhui 230601 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institutes of Physical Science and Information Technology and School of Computer Science and Technology, Anhui University , Hefei, Anhui 230601 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lihong","family":"Yu","sequence":"additional","affiliation":[{"name":"GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Medical University , Guangzhou, Guangdong 511436 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun-Hou","family":"Zheng","sequence":"additional","affiliation":[{"name":"Institutes of Physical Science and Information Technology and School of Computer Science and Technology, Anhui University , Hefei, Anhui 230601 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenguang","family":"Yin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University , Guangzhou 510180 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3024-1705","authenticated-orcid":false,"given":"Junfeng","family":"Xia","sequence":"additional","affiliation":[{"name":"Institutes of Physical Science and Information Technology and School of Computer Science and Technology, Anhui University , Hefei, Anhui 230601 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7683-590X","authenticated-orcid":false,"given":"Tiejun","family":"Zhang","sequence":"additional","affiliation":[{"name":"GMU-GIBH Joint School of Life 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