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HotSwap for bioinformatics: A STRAP tutorial

BACKGROUND: Bioinformatics applications are now routinely used to analyze large amounts of data. Application development often requires many cycles of optimization, compiling, and testing. Repeatedly loading large datasets can significantly slow down the development process. We have incorporated Hot...

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Detalles Bibliográficos
Autores principales: Gille, Christoph, Robinson, Peter N
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1386713/
https://www.ncbi.nlm.nih.gov/pubmed/16469097
http://dx.doi.org/10.1186/1471-2105-7-64
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author Gille, Christoph
Robinson, Peter N
author_facet Gille, Christoph
Robinson, Peter N
author_sort Gille, Christoph
collection PubMed
description BACKGROUND: Bioinformatics applications are now routinely used to analyze large amounts of data. Application development often requires many cycles of optimization, compiling, and testing. Repeatedly loading large datasets can significantly slow down the development process. We have incorporated HotSwap functionality into the protein workbench STRAP, allowing developers to create plugins using the Java HotSwap technique. RESULTS: Users can load multiple protein sequences or structures into the main STRAP user interface, and simultaneously develop plugins using an editor of their choice such as Emacs. Saving changes to the Java file causes STRAP to recompile the plugin and automatically update its user interface without requiring recompilation of STRAP or reloading of protein data. This article presents a tutorial on how to develop HotSwap plugins. STRAP is available at and . CONCLUSION: HotSwap is a useful and time-saving technique for bioinformatics developers. HotSwap can be used to efficiently develop bioinformatics applications that require loading large amounts of data into memory.
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spelling pubmed-13867132006-03-02 HotSwap for bioinformatics: A STRAP tutorial Gille, Christoph Robinson, Peter N BMC Bioinformatics Methodology Article BACKGROUND: Bioinformatics applications are now routinely used to analyze large amounts of data. Application development often requires many cycles of optimization, compiling, and testing. Repeatedly loading large datasets can significantly slow down the development process. We have incorporated HotSwap functionality into the protein workbench STRAP, allowing developers to create plugins using the Java HotSwap technique. RESULTS: Users can load multiple protein sequences or structures into the main STRAP user interface, and simultaneously develop plugins using an editor of their choice such as Emacs. Saving changes to the Java file causes STRAP to recompile the plugin and automatically update its user interface without requiring recompilation of STRAP or reloading of protein data. This article presents a tutorial on how to develop HotSwap plugins. STRAP is available at and . CONCLUSION: HotSwap is a useful and time-saving technique for bioinformatics developers. HotSwap can be used to efficiently develop bioinformatics applications that require loading large amounts of data into memory. BioMed Central 2006-02-09 /pmc/articles/PMC1386713/ /pubmed/16469097 http://dx.doi.org/10.1186/1471-2105-7-64 Text en Copyright © 2006 Gille and Robinson; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Gille, Christoph
Robinson, Peter N
HotSwap for bioinformatics: A STRAP tutorial
title HotSwap for bioinformatics: A STRAP tutorial
title_full HotSwap for bioinformatics: A STRAP tutorial
title_fullStr HotSwap for bioinformatics: A STRAP tutorial
title_full_unstemmed HotSwap for bioinformatics: A STRAP tutorial
title_short HotSwap for bioinformatics: A STRAP tutorial
title_sort hotswap for bioinformatics: a strap tutorial
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1386713/
https://www.ncbi.nlm.nih.gov/pubmed/16469097
http://dx.doi.org/10.1186/1471-2105-7-64
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