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Therefore, the accurate prediction of ACPs is of great significance to the research of cancer diseases. In the paper, we developed a more efficient prediction model called ACP_MS. Firstly, the monoMonoKGap method is used to extract the characteristic of anticancer peptide sequences and form the digital features. Then, the AdaBoost model is used to select the most discriminating features from the digital features. Finally, a stochastic gradient descent algorithm is introduced to identify anticancer peptide sequences. We adopt 7-fold cross-validation and independent test set validation, and the final accuracy of the main dataset reached 92.653% and 91.597%, respectively. The accuracy of the alternate dataset reached 98.678% and 98.317%, respectively. Compared with other advanced prediction models, the ACP_MS model improves the identification ability of anticancer peptide sequences. The data of this model can be downloaded from the public website for free https:\/\/github.com\/Zhoucaimao1998\/Zc<\/jats:p>","DOI":"10.1093\/bib\/bbac462","type":"journal-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T10:52:53Z","timestamp":1667472773000},"source":"Crossref","is-referenced-by-count":16,"title":["ACP_MS: prediction of anticancer peptides based on feature extraction"],"prefix":"10.1093","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9317-5074","authenticated-orcid":false,"given":"Caimao","family":"Zhou","sequence":"first","affiliation":[{"name":"Key Laboratory of Computational Science and Application of Hainan Province , Haikou, China"},{"name":"Key Laboratory of Data Science and Intelligence Education, Hainan Normal University, Ministry of Education , Haikou, China"},{"name":"School of Mathematics and Statistics, Hainan Normal University , Haikou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dejun","family":"Peng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Computational Science and Application of Hainan Province , Haikou, China"},{"name":"Key Laboratory of Data Science and Intelligence Education, Hainan Normal University, Ministry of Education , Haikou, China"},{"name":"School of Mathematics and Statistics, Hainan Normal University , Haikou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Liao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Computational Science and Application of Hainan Province , Haikou, China"},{"name":"Key Laboratory of Data Science and Intelligence Education, Hainan Normal University, Ministry of Education , Haikou, China"},{"name":"School of Mathematics and Statistics, Hainan Normal University , Haikou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ranran","family":"Jia","sequence":"additional","affiliation":[{"name":"Key Laboratory of Computational Science and Application of Hainan Province , Haikou, China"},{"name":"Key Laboratory of Data Science and Intelligence Education, Hainan Normal University, Ministry of Education , Haikou, China"},{"name":"School of Mathematics and Statistics, Hainan Normal University , Haikou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fangxiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Computational Science and Application of Hainan Province , Haikou, China"},{"name":"Key Laboratory of Data Science and Intelligence Education, Hainan Normal University, Ministry of Education , Haikou, China"},{"name":"School of Mathematics and Statistics, Hainan Normal University , Haikou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,11,2]]},"reference":[{"issue":"2","key":"2022112111194780500_ref1","doi-asserted-by":"crossref","first-page":"54","DOI":"10.3390\/pharmaceutics10020054","article-title":"Anticancer activity of bacterial proteins and peptides","volume":"10","author":"Karpi\u0144ski","year":"2018","journal-title":"Pharmaceutics"},{"issue":"1","key":"2022112111194780500_ref2","doi-asserted-by":"crossref","first-page":"57","DOI":"10.2174\/1574893611666160609081155","article-title":"Cancer diagnosis through isomiR expression with machine learning method","volume":"13","author":"Liao","year":"2018","journal-title":"Curr Bioinform"},{"issue":"3","key":"2022112111194780500_ref3","doi-asserted-by":"crossref","first-page":"158","DOI":"10.3390\/genes9030158","article-title":"A novel hybrid sequence-based model for identifying anticancer peptides","volume":"9","author":"Xu","year":"2018","journal-title":"Genes"},{"key":"2022112111194780500_ref4","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1016\/j.omtn.2020.10.005","article-title":"Deepacp: a novel computational approach for accurate identification of anticancer peptides by deep learning algorithm","volume":"22","author":"Yu","year":"2020","journal-title":"Mol Ther Nucleic Acids"},{"key":"2022112111194780500_ref5","doi-asserted-by":"crossref","first-page":"394","DOI":"10.3322\/caac.21492","article-title":"Global cancer statistics 2018: Globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"68","author":"Bray","year":"2018","journal-title":"CA Cancer J Clin"},{"issue":"2","key":"2022112111194780500_ref6","article-title":"Combining epigenetic drugs with other therapies for solid tumours \u2014 past lessons and future promise. 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