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However, the specific characterization for cancerlectins involved in tumor progression is still unclear. By taking advantage of the g-gap tripeptide and tetrapeptide composition feature descriptors, we increased the accuracy of the classification model of cancerlectin and lectin to 98.54% and 95.38%, respectively. About 36 cancerlectin and 135 lectin features were selected for functional characterization by P\/N feature ranking method, which particularly selects the features in positive samples. The specific protein domains of cancerlectins are found to be p-GalNAc-T, crystal and annexin by comparing with lectins through the exclusion method. Moreover, the combined GO analysis showed that the conserved cation binding sites of cancerlectin specific domains are covered by selected feature peptides, suggesting that the capability of cation binding, critical for enzyme activity and stability, could be the key characteristic of cancerlectins in tumor progression. These results will help to identify potential cancerlectin and provide clues for mechanism study of cancerlectin in tumor progression.<\/jats:p>","DOI":"10.1093\/bib\/bbab227","type":"journal-article","created":{"date-parts":[[2021,5,26]],"date-time":"2021-05-26T11:11:23Z","timestamp":1622027483000},"source":"Crossref","is-referenced-by-count":6,"title":["The accurate prediction and characterization of cancerlectin by a combined machine learning and GO analysis"],"prefix":"10.1093","volume":"22","author":[{"given":"Furong","family":"Tang","sequence":"first","affiliation":[{"name":"School of Electronic and Communication Engineering, Shenzhen Polytechnic, Shenzhen 518000, China"},{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lichao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Intelligent Manufacturing and Equipment, Shenzhen Institute of Information Technology, Shenzhen 518172, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Electronic and Communication Engineering, Shenzhen Polytechnic, Shenzhen 518000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quan","family":"Zou","sequence":"additional","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hailin","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Information Engineering Zhejiang A&F University, Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Hangzhou, Zhejiang 311300, 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