Jaewoo Lee, Mehita Achuthan, Lucas Chen, Paulina Carmona-Mora
{"title":"可定制的安全 DIY 网络应用程序,用于访问、共享和浏览综合实验结果和元数据。","authors":"Jaewoo Lee, Mehita Achuthan, Lucas Chen, Paulina Carmona-Mora","doi":"10.1093/bioadv/vbae087","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>A problem spanning across many research fields is that processed data and research results are often scattered, which makes data access, analysis, extraction, and team sharing more challenging. We have developed a platform for researchers to easily manage tabular data with features like browsing, bookmarking, and linking to external open knowledge bases. The source code, originally designed for genomics research, is customizable for use by other fields or data, providing a no- to low-cost DIY system for research teams.</p><p><strong>Availability and implementation: </strong>The source code of our DIY app is available on https://github.com/Carmona-MoraUCD/Human-Genomics-Browser. It can be downloaded and run by anyone with a web browser, Python3, and Node.js on their machine. The web application is licensed under the MIT license.</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11257709/pdf/","citationCount":"0","resultStr":"{\"title\":\"A customizable secure DIY web application for accessing, sharing, and browsing aggregate experimental results and metadata.\",\"authors\":\"Jaewoo Lee, Mehita Achuthan, Lucas Chen, Paulina Carmona-Mora\",\"doi\":\"10.1093/bioadv/vbae087\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Summary: </strong>A problem spanning across many research fields is that processed data and research results are often scattered, which makes data access, analysis, extraction, and team sharing more challenging. We have developed a platform for researchers to easily manage tabular data with features like browsing, bookmarking, and linking to external open knowledge bases. The source code, originally designed for genomics research, is customizable for use by other fields or data, providing a no- to low-cost DIY system for research teams.</p><p><strong>Availability and implementation: </strong>The source code of our DIY app is available on https://github.com/Carmona-MoraUCD/Human-Genomics-Browser. It can be downloaded and run by anyone with a web browser, Python3, and Node.js on their machine. The web application is licensed under the MIT license.</p>\",\"PeriodicalId\":72368,\"journal\":{\"name\":\"Bioinformatics advances\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11257709/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bioinformatics advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/bioadv/vbae087\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbae087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
A customizable secure DIY web application for accessing, sharing, and browsing aggregate experimental results and metadata.
Summary: A problem spanning across many research fields is that processed data and research results are often scattered, which makes data access, analysis, extraction, and team sharing more challenging. We have developed a platform for researchers to easily manage tabular data with features like browsing, bookmarking, and linking to external open knowledge bases. The source code, originally designed for genomics research, is customizable for use by other fields or data, providing a no- to low-cost DIY system for research teams.
Availability and implementation: The source code of our DIY app is available on https://github.com/Carmona-MoraUCD/Human-Genomics-Browser. It can be downloaded and run by anyone with a web browser, Python3, and Node.js on their machine. The web application is licensed under the MIT license.