{"title":"Some New Attempts to Process Biological Data","authors":"Shuxun Yang, Mingpu Li, Jun Luo, Yupeng Lu, Chao Yan, Xu-Qing Tang","doi":"10.1109/DCABES50732.2020.00084","DOIUrl":null,"url":null,"abstract":"The purpose of this paper is to realize system analysis and algorithm design for biological data. In this paper, primary bladder cancer is taken as a typical example, the structure of the system is extracted by hierarchical clustering method, and the function of the system is mined by convolutional neural network technology. Based on these methods, a complex system structure analysis model and an algorithm are constructed to study the big data system. Furthermore, the feasibility study of relevant theories and methods are carried out while the application and expand of technology are mentioned, combined with the actual data. The effectiveness and practicability of the algorithm and system are also verified by simulation.","PeriodicalId":351404,"journal":{"name":"2020 19th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 19th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCABES50732.2020.00084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The purpose of this paper is to realize system analysis and algorithm design for biological data. In this paper, primary bladder cancer is taken as a typical example, the structure of the system is extracted by hierarchical clustering method, and the function of the system is mined by convolutional neural network technology. Based on these methods, a complex system structure analysis model and an algorithm are constructed to study the big data system. Furthermore, the feasibility study of relevant theories and methods are carried out while the application and expand of technology are mentioned, combined with the actual data. The effectiveness and practicability of the algorithm and system are also verified by simulation.