{"title":"在数据库框架内无缝集成生物应用程序。","authors":"T Topaloglou, A Kosky, V Markowitz","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>There are more than two hundred biological data repositories available for public access, and a vast number of applications to process and interpret biological data. A major challenge for bioinformaticians is to extract and process data from multiple data sources using a variety of query interfaces and analytical tools. In this paper, we describe tools that respond to this challenge by providing support for cross-database queries and for integrating analytical tools in a query processing environment. In particular, we describe two alternative methods for integrating biological data processing within traditional database queries: (a) \"light-weight\" application integration based on Application Specific Data Types (ASDTs) and (b) \"heavy-duty\" integration of analytical tools based on mediators and wrappers. These methods are supported by the Object-Protocol Model (OPM) suite of tools for managing biological databases.</p>","PeriodicalId":79420,"journal":{"name":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1999-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Seamless integration of biological applications within a database framework.\",\"authors\":\"T Topaloglou, A Kosky, V Markowitz\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>There are more than two hundred biological data repositories available for public access, and a vast number of applications to process and interpret biological data. A major challenge for bioinformaticians is to extract and process data from multiple data sources using a variety of query interfaces and analytical tools. In this paper, we describe tools that respond to this challenge by providing support for cross-database queries and for integrating analytical tools in a query processing environment. In particular, we describe two alternative methods for integrating biological data processing within traditional database queries: (a) \\\"light-weight\\\" application integration based on Application Specific Data Types (ASDTs) and (b) \\\"heavy-duty\\\" integration of analytical tools based on mediators and wrappers. These methods are supported by the Object-Protocol Model (OPM) suite of tools for managing biological databases.</p>\",\"PeriodicalId\":79420,\"journal\":{\"name\":\"Proceedings. International Conference on Intelligent Systems for Molecular Biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. International Conference on Intelligent Systems for Molecular Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Seamless integration of biological applications within a database framework.
There are more than two hundred biological data repositories available for public access, and a vast number of applications to process and interpret biological data. A major challenge for bioinformaticians is to extract and process data from multiple data sources using a variety of query interfaces and analytical tools. In this paper, we describe tools that respond to this challenge by providing support for cross-database queries and for integrating analytical tools in a query processing environment. In particular, we describe two alternative methods for integrating biological data processing within traditional database queries: (a) "light-weight" application integration based on Application Specific Data Types (ASDTs) and (b) "heavy-duty" integration of analytical tools based on mediators and wrappers. These methods are supported by the Object-Protocol Model (OPM) suite of tools for managing biological databases.