{"title":"用于简化遗传分析工具开发的敏捷模型驱动方法","authors":"M. Villanueva","doi":"10.1109/RCIS.2012.6240414","DOIUrl":null,"url":null,"abstract":"In the last few years, genetic researchers have started to assemble their own genetic analysis tools by reusing and combining available software. Because software development environments are not widely accepted in the Genetics community, geneticists become software developers, and they are force to integrate different solutions and to face programming issues without the required knowledge. A solution to this issue lives in the simplification of the tailored tool development. Geneticists demand development environments where: 1) the required data can be expressed according to their knowledge, and 2) the most common functionality can be easily integrated without programming skills. This PhD work proposes the use of the model-driven paradigm for addressing both concerns and presents an agile way for developing genetic analysis tools.","PeriodicalId":130476,"journal":{"name":"2012 Sixth International Conference on Research Challenges in Information Science (RCIS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An agile model-driven approach for simplifying the development of genetic analysis tools\",\"authors\":\"M. Villanueva\",\"doi\":\"10.1109/RCIS.2012.6240414\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the last few years, genetic researchers have started to assemble their own genetic analysis tools by reusing and combining available software. Because software development environments are not widely accepted in the Genetics community, geneticists become software developers, and they are force to integrate different solutions and to face programming issues without the required knowledge. A solution to this issue lives in the simplification of the tailored tool development. Geneticists demand development environments where: 1) the required data can be expressed according to their knowledge, and 2) the most common functionality can be easily integrated without programming skills. This PhD work proposes the use of the model-driven paradigm for addressing both concerns and presents an agile way for developing genetic analysis tools.\",\"PeriodicalId\":130476,\"journal\":{\"name\":\"2012 Sixth International Conference on Research Challenges in Information Science (RCIS)\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Sixth International Conference on Research Challenges in Information Science (RCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RCIS.2012.6240414\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Sixth International Conference on Research Challenges in Information Science (RCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RCIS.2012.6240414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An agile model-driven approach for simplifying the development of genetic analysis tools
In the last few years, genetic researchers have started to assemble their own genetic analysis tools by reusing and combining available software. Because software development environments are not widely accepted in the Genetics community, geneticists become software developers, and they are force to integrate different solutions and to face programming issues without the required knowledge. A solution to this issue lives in the simplification of the tailored tool development. Geneticists demand development environments where: 1) the required data can be expressed according to their knowledge, and 2) the most common functionality can be easily integrated without programming skills. This PhD work proposes the use of the model-driven paradigm for addressing both concerns and presents an agile way for developing genetic analysis tools.