{"title":"Physiological signal analysis and open science using the Julia language and associated software.","authors":"George Datseris, Jacob S Zelko","doi":"10.3389/fnetp.2024.1478280","DOIUrl":null,"url":null,"abstract":"<p><p>In this mini review, we propose the use of the Julia programming language and its software as a strong candidate for reproducible, efficient, and sustainable physiological signal analysis. First, we highlight available software and Julia communities that provide top-of-the-class algorithms for all aspects of physiological signal processing despite the language's relatively young age. Julia can significantly accelerate both research and software development due to its high-level interactive language and high-performance code generation. It is also particularly suited for open and reproducible science. Openness is supported and welcomed because the overwhelming majority of Julia software programs are open source and developed openly on public platforms, primarily through individual contributions. Such an environment increases the likelihood that an individual not (originally) associated with a software program would still be willing to contribute their code, further promoting code sharing and reuse. On the other hand, Julia's exceptionally strong package manager and surrounding ecosystem make it easy to create self-contained, reproducible projects that can be instantly installed and run, irrespective of processor architecture or operating system.</p>","PeriodicalId":73092,"journal":{"name":"Frontiers in network physiology","volume":"4 ","pages":"1478280"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11577965/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in network physiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fnetp.2024.1478280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this mini review, we propose the use of the Julia programming language and its software as a strong candidate for reproducible, efficient, and sustainable physiological signal analysis. First, we highlight available software and Julia communities that provide top-of-the-class algorithms for all aspects of physiological signal processing despite the language's relatively young age. Julia can significantly accelerate both research and software development due to its high-level interactive language and high-performance code generation. It is also particularly suited for open and reproducible science. Openness is supported and welcomed because the overwhelming majority of Julia software programs are open source and developed openly on public platforms, primarily through individual contributions. Such an environment increases the likelihood that an individual not (originally) associated with a software program would still be willing to contribute their code, further promoting code sharing and reuse. On the other hand, Julia's exceptionally strong package manager and surrounding ecosystem make it easy to create self-contained, reproducible projects that can be instantly installed and run, irrespective of processor architecture or operating system.
在这篇小型综述中,我们建议将 Julia 编程语言及其软件作为可重复、高效和可持续生理信号分析的有力候选工具。首先,我们将重点介绍现有的软件和 Julia 社区,这些软件和社区为生理信号处理的各个方面提供了一流的算法,尽管 Julia 语言还相对年轻。Julia 凭借其高级交互式语言和高性能代码生成,可以大大加快研究和软件开发的速度。它还特别适用于开放和可重复的科学。开放性之所以受到支持和欢迎,是因为绝大多数Julia软件程序都是开源的,并主要通过个人贡献在公共平台上公开开发。这样的环境增加了(原本)与软件程序无关的个人仍然愿意贡献代码的可能性,进一步促进了代码共享和重用。另一方面,Julia 极其强大的软件包管理器和周边生态系统使创建自包含、可重现的项目变得非常容易,无论处理器架构或操作系统如何,这些项目都可以立即安装和运行。