Jaewoo Lee, Mehita Achuthan, Lucas Chen, Paulina Carmona-Mora
{"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}
引用次数: 0
Abstract
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.
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