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Sharing Programming Resources Between Bio* Projects
Open-source software encourages computer programmers to reuse software components written by others. In evolutionary bioinformatics, open-source software comes in a broad range of programming languages, including C/C++, Perl, Python, Ruby, Java, and R. To avoid writing the same functionality multipl...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7212028/ https://www.ncbi.nlm.nih.gov/pubmed/31278684 http://dx.doi.org/10.1007/978-1-4939-9074-0_25 |
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author | Bonnal, Raoul J. P. Yates, Andrew Goto, Naohisa Gautier, Laurent Willis, Scooter Fields, Christopher Katayama, Toshiaki Prins, Pjotr |
author_facet | Bonnal, Raoul J. P. Yates, Andrew Goto, Naohisa Gautier, Laurent Willis, Scooter Fields, Christopher Katayama, Toshiaki Prins, Pjotr |
author_sort | Bonnal, Raoul J. P. |
collection | PubMed |
description | Open-source software encourages computer programmers to reuse software components written by others. In evolutionary bioinformatics, open-source software comes in a broad range of programming languages, including C/C++, Perl, Python, Ruby, Java, and R. To avoid writing the same functionality multiple times for different languages, it is possible to share components by bridging computer languages and Bio* projects, such as BioPerl, Biopython, BioRuby, BioJava, and R/Bioconductor. In this chapter, we compare the three principal approaches for sharing software between different programming languages: by remote procedure call (RPC), by sharing a local “call stack,” and by calling program to programs. RPC provides a language-independent protocol over a network interface; examples are SOAP and Rserve. The local call stack provides a between-language mapping, not over the network interface but directly in computer memory; examples are R bindings, RPy, and languages sharing the Java virtual machine stack. This functionality provides strategies for sharing of software between Bio* projects, which can be exploited more often. Here, we present cross-language examples for sequence translation and measure throughput of the different options. We compare calling into R through native R, RSOAP, Rserve, and RPy interfaces, with the performance of native BioPerl, Biopython, BioJava, and BioRuby implementations and with call stack bindings to BioJava and the European Molecular Biology Open Software Suite (EMBOSS). In general, call stack approaches outperform native Bio* implementations, and these, in turn, outperform “RPC”-based approaches. To test and compare strategies, we provide a downloadable Docker container with all examples, tools, and libraries included. |
format | Online Article Text |
id | pubmed-7212028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72120282020-05-11 Sharing Programming Resources Between Bio* Projects Bonnal, Raoul J. P. Yates, Andrew Goto, Naohisa Gautier, Laurent Willis, Scooter Fields, Christopher Katayama, Toshiaki Prins, Pjotr Methods Mol Biol Article Open-source software encourages computer programmers to reuse software components written by others. In evolutionary bioinformatics, open-source software comes in a broad range of programming languages, including C/C++, Perl, Python, Ruby, Java, and R. To avoid writing the same functionality multiple times for different languages, it is possible to share components by bridging computer languages and Bio* projects, such as BioPerl, Biopython, BioRuby, BioJava, and R/Bioconductor. In this chapter, we compare the three principal approaches for sharing software between different programming languages: by remote procedure call (RPC), by sharing a local “call stack,” and by calling program to programs. RPC provides a language-independent protocol over a network interface; examples are SOAP and Rserve. The local call stack provides a between-language mapping, not over the network interface but directly in computer memory; examples are R bindings, RPy, and languages sharing the Java virtual machine stack. This functionality provides strategies for sharing of software between Bio* projects, which can be exploited more often. Here, we present cross-language examples for sequence translation and measure throughput of the different options. We compare calling into R through native R, RSOAP, Rserve, and RPy interfaces, with the performance of native BioPerl, Biopython, BioJava, and BioRuby implementations and with call stack bindings to BioJava and the European Molecular Biology Open Software Suite (EMBOSS). In general, call stack approaches outperform native Bio* implementations, and these, in turn, outperform “RPC”-based approaches. To test and compare strategies, we provide a downloadable Docker container with all examples, tools, and libraries included. 2019-01-01 /pmc/articles/PMC7212028/ /pubmed/31278684 http://dx.doi.org/10.1007/978-1-4939-9074-0_25 Text en http://creativecommons.org/licenses/by/4.0/ This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. |
spellingShingle | Article Bonnal, Raoul J. P. Yates, Andrew Goto, Naohisa Gautier, Laurent Willis, Scooter Fields, Christopher Katayama, Toshiaki Prins, Pjotr Sharing Programming Resources Between Bio* Projects |
title | Sharing Programming Resources Between Bio* Projects |
title_full | Sharing Programming Resources Between Bio* Projects |
title_fullStr | Sharing Programming Resources Between Bio* Projects |
title_full_unstemmed | Sharing Programming Resources Between Bio* Projects |
title_short | Sharing Programming Resources Between Bio* Projects |
title_sort | sharing programming resources between bio* projects |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7212028/ https://www.ncbi.nlm.nih.gov/pubmed/31278684 http://dx.doi.org/10.1007/978-1-4939-9074-0_25 |
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