Guoli Ji, Yang Lin, Qianmin Lin, Guangzao Huang, Wenbing Zhu, Wenjie You
{"title":"利用特征融合和MSVM-RFE预测dna结合蛋白","authors":"Guoli Ji, Yang Lin, Qianmin Lin, Guangzao Huang, Wenbing Zhu, Wenjie You","doi":"10.1109/ICASID.2016.7873928","DOIUrl":null,"url":null,"abstract":"DNA-binding proteins play a vital important role in cell activities. Prediction of DNA-binding proteins is an important but not fairly solved problem. Currently prediction of DNA-binding proteins via calculation method is a research hotspot. In this paper, we adopt MSVM-RFE for feature selection to those high-dimensional features generated in multiclass feature fusion process and obtain a representative feature subset. The feature subset is evaluated by thirty times 10-fold cross-validation test. At last, we verified the effectiveness of this method compared with method DNA-Prot and other method through three typical datasets. The results demonstrate that this method of predicting DNA-binding proteins has better effect.","PeriodicalId":294777,"journal":{"name":"2016 10th IEEE International Conference on Anti-counterfeiting, Security, and Identification (ASID)","volume":"2676 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Predicting DNA-binding proteins using feature fusion and MSVM-RFE\",\"authors\":\"Guoli Ji, Yang Lin, Qianmin Lin, Guangzao Huang, Wenbing Zhu, Wenjie You\",\"doi\":\"10.1109/ICASID.2016.7873928\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"DNA-binding proteins play a vital important role in cell activities. Prediction of DNA-binding proteins is an important but not fairly solved problem. Currently prediction of DNA-binding proteins via calculation method is a research hotspot. In this paper, we adopt MSVM-RFE for feature selection to those high-dimensional features generated in multiclass feature fusion process and obtain a representative feature subset. The feature subset is evaluated by thirty times 10-fold cross-validation test. At last, we verified the effectiveness of this method compared with method DNA-Prot and other method through three typical datasets. The results demonstrate that this method of predicting DNA-binding proteins has better effect.\",\"PeriodicalId\":294777,\"journal\":{\"name\":\"2016 10th IEEE International Conference on Anti-counterfeiting, Security, and Identification (ASID)\",\"volume\":\"2676 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 10th IEEE International Conference on Anti-counterfeiting, Security, and Identification (ASID)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASID.2016.7873928\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 10th IEEE International Conference on Anti-counterfeiting, Security, and Identification (ASID)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASID.2016.7873928","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predicting DNA-binding proteins using feature fusion and MSVM-RFE
DNA-binding proteins play a vital important role in cell activities. Prediction of DNA-binding proteins is an important but not fairly solved problem. Currently prediction of DNA-binding proteins via calculation method is a research hotspot. In this paper, we adopt MSVM-RFE for feature selection to those high-dimensional features generated in multiclass feature fusion process and obtain a representative feature subset. The feature subset is evaluated by thirty times 10-fold cross-validation test. At last, we verified the effectiveness of this method compared with method DNA-Prot and other method through three typical datasets. The results demonstrate that this method of predicting DNA-binding proteins has better effect.