{"title":"CPSNF:具有新特征的蛋白质结构分类","authors":"Hong-Xuan Hua","doi":"10.1109/SPAC46244.2018.8965568","DOIUrl":null,"url":null,"abstract":"Protein structures play key roles in many fields of biology. However, identification of protein structural types from protein sequences seems to be a challenge issue. In this study, several novel reconstructed features have been proposed and employed to be the features to deal with the machine learning issue. So as to demonstrate the performance of these features, 10-fold has been utilized in two benchmark datasets, including 1189 and 25PDB. Our proposed features can be effective to deal with the four types of protein tertiary structure than other art-of-the-state methods.","PeriodicalId":360369,"journal":{"name":"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CPSNF: Classification of Protein Structure with Novel Features\",\"authors\":\"Hong-Xuan Hua\",\"doi\":\"10.1109/SPAC46244.2018.8965568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Protein structures play key roles in many fields of biology. However, identification of protein structural types from protein sequences seems to be a challenge issue. In this study, several novel reconstructed features have been proposed and employed to be the features to deal with the machine learning issue. So as to demonstrate the performance of these features, 10-fold has been utilized in two benchmark datasets, including 1189 and 25PDB. Our proposed features can be effective to deal with the four types of protein tertiary structure than other art-of-the-state methods.\",\"PeriodicalId\":360369,\"journal\":{\"name\":\"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPAC46244.2018.8965568\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAC46244.2018.8965568","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CPSNF: Classification of Protein Structure with Novel Features
Protein structures play key roles in many fields of biology. However, identification of protein structural types from protein sequences seems to be a challenge issue. In this study, several novel reconstructed features have been proposed and employed to be the features to deal with the machine learning issue. So as to demonstrate the performance of these features, 10-fold has been utilized in two benchmark datasets, including 1189 and 25PDB. Our proposed features can be effective to deal with the four types of protein tertiary structure than other art-of-the-state methods.