{"title":"利用结构特征预测蛋白质的β -片数","authors":"Amir Hossein Babolhakami, Behshid Behkamal, Toktam Dehghani, Kobra Etminani, Mahmoud Naghibzadeh","doi":"10.1109/ICCKE.2017.8167921","DOIUrl":null,"url":null,"abstract":"A protein is a long one-dimensional amino acid sequence. Some subsequences of this sequence are given names and β-strand in one such subsequence. β-strands are very common and two or more such strands within one protein can form a β-sheet in the secondary structure of proteins. In its natural form, a protein is a three-dimensional entity composed of β-sheets, α-helices, and other types of substructures. Knowing the exact three-dimensional structure of a protein is the key to diagnosing several diseases and producing some drugs. In many proteins, β-sheets are the most common and the dominating substructure. Predicting the number of β-sheets in a given protein sequence is a valuable step in predicting the whole β-sheets structure in the sense that it can reduce the time complexity of the exhaustive search space examination predictors. In this research, a data-mining method for predicting the number of β-sheets is developed. The evaluations show that its performance is highly reliable.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Protein's number of beta-sheets prediction using structural features\",\"authors\":\"Amir Hossein Babolhakami, Behshid Behkamal, Toktam Dehghani, Kobra Etminani, Mahmoud Naghibzadeh\",\"doi\":\"10.1109/ICCKE.2017.8167921\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A protein is a long one-dimensional amino acid sequence. Some subsequences of this sequence are given names and β-strand in one such subsequence. β-strands are very common and two or more such strands within one protein can form a β-sheet in the secondary structure of proteins. In its natural form, a protein is a three-dimensional entity composed of β-sheets, α-helices, and other types of substructures. Knowing the exact three-dimensional structure of a protein is the key to diagnosing several diseases and producing some drugs. In many proteins, β-sheets are the most common and the dominating substructure. Predicting the number of β-sheets in a given protein sequence is a valuable step in predicting the whole β-sheets structure in the sense that it can reduce the time complexity of the exhaustive search space examination predictors. In this research, a data-mining method for predicting the number of β-sheets is developed. The evaluations show that its performance is highly reliable.\",\"PeriodicalId\":151934,\"journal\":{\"name\":\"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCKE.2017.8167921\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCKE.2017.8167921","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Protein's number of beta-sheets prediction using structural features
A protein is a long one-dimensional amino acid sequence. Some subsequences of this sequence are given names and β-strand in one such subsequence. β-strands are very common and two or more such strands within one protein can form a β-sheet in the secondary structure of proteins. In its natural form, a protein is a three-dimensional entity composed of β-sheets, α-helices, and other types of substructures. Knowing the exact three-dimensional structure of a protein is the key to diagnosing several diseases and producing some drugs. In many proteins, β-sheets are the most common and the dominating substructure. Predicting the number of β-sheets in a given protein sequence is a valuable step in predicting the whole β-sheets structure in the sense that it can reduce the time complexity of the exhaustive search space examination predictors. In this research, a data-mining method for predicting the number of β-sheets is developed. The evaluations show that its performance is highly reliable.