Physiological signal analysis and open science using the Julia language and associated software
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 a...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Network Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnetp.2024.1478280/full |
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| author | George Datseris Jacob S. Zelko Jacob S. Zelko |
| author_facet | George Datseris Jacob S. Zelko Jacob S. Zelko |
| author_sort | George Datseris |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-dbc8c84fa7694d7fbfa07b6190fe4ad9 |
| institution | DOAJ |
| issn | 2674-0109 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Network Physiology |
| spelling | doaj-art-dbc8c84fa7694d7fbfa07b6190fe4ad92025-08-20T02:49:47ZengFrontiers Media S.A.Frontiers in Network Physiology2674-01092024-11-01410.3389/fnetp.2024.14782801478280Physiological signal analysis and open science using the Julia language and associated softwareGeorge Datseris0Jacob S. Zelko1Jacob S. Zelko2Department of Mathematics and Statistics, University of Exeter, Exeter, United KingdomDepartment of Mathematics, Northeastern University, Boston, MA, United StatesOHDSI Center, Roux Institute, Northeastern University, Portland, ME, United StatesIn 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.https://www.frontiersin.org/articles/10.3389/fnetp.2024.1478280/fulldigital signal processingphysiological signalscomplexity measuresJuliatime series analysisreproducible |
| spellingShingle | George Datseris Jacob S. Zelko Jacob S. Zelko Physiological signal analysis and open science using the Julia language and associated software Frontiers in Network Physiology digital signal processing physiological signals complexity measures Julia time series analysis reproducible |
| title | Physiological signal analysis and open science using the Julia language and associated software |
| title_full | Physiological signal analysis and open science using the Julia language and associated software |
| title_fullStr | Physiological signal analysis and open science using the Julia language and associated software |
| title_full_unstemmed | Physiological signal analysis and open science using the Julia language and associated software |
| title_short | Physiological signal analysis and open science using the Julia language and associated software |
| title_sort | physiological signal analysis and open science using the julia language and associated software |
| topic | digital signal processing physiological signals complexity measures Julia time series analysis reproducible |
| url | https://www.frontiersin.org/articles/10.3389/fnetp.2024.1478280/full |
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