M. Mirto, S. Fiore, M. Cafaro, Marco Passante, G. Aloisio
{"title":"A Grid-Based Bioinformatics Wrapper for Biological Databases","authors":"M. Mirto, S. Fiore, M. Cafaro, Marco Passante, G. Aloisio","doi":"10.1109/CBMS.2008.93","DOIUrl":null,"url":null,"abstract":"With a growing trend towards grid-based data repositories and data analysis services, scientific data analysis often involves accessing multiple data sources, and analyzing the data using a variety of analysis programs. A strictly related critical challenge is the fact that data sources often hold the same type of data in a number of different formats; moreover, the formats expected and generated by various data analysis services are often distinct. In bioinformatics the data are often stored in flat files, therefore accessing them to retrieve a subset of records determined by constraints, is slower with respect to other approaches such as relational DBMS. We have developed a data grid system, built on top of specific biological data sources in flat file format, which carries out the ingestion into a relational DBMS for data integration reducing the data redundancy present in the biological flat files. In this work, we describe the prototype for the ingestion in a relational DBMS of the Swiss-2D PAGE flat file.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"276 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2008.93","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
With a growing trend towards grid-based data repositories and data analysis services, scientific data analysis often involves accessing multiple data sources, and analyzing the data using a variety of analysis programs. A strictly related critical challenge is the fact that data sources often hold the same type of data in a number of different formats; moreover, the formats expected and generated by various data analysis services are often distinct. In bioinformatics the data are often stored in flat files, therefore accessing them to retrieve a subset of records determined by constraints, is slower with respect to other approaches such as relational DBMS. We have developed a data grid system, built on top of specific biological data sources in flat file format, which carries out the ingestion into a relational DBMS for data integration reducing the data redundancy present in the biological flat files. In this work, we describe the prototype for the ingestion in a relational DBMS of the Swiss-2D PAGE flat file.