Difference between revisions of "BioUML"
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| − | BioUML is an open source integrated Java platform for analysis of data from omics sciences research and other advanced computational biology, for building the [[virtual cell]] and the | + | BioUML is an open source integrated Java platform for analysis of data from omics sciences research and other advanced computational biology, for building the [[virtual cell]] and the [http://en.wikipedia.org/wiki/Virtual_Physiological_Human virtual physiological human]. It spans a comprehensive range of capabilities, including access to databases with experimental data, tools for formalized description of biological systems structure and functioning, as well as tools for their visualization, simulation, parameters fitting and analyses. Due to scripts (R, JavaScript) and workflow support it provides powerful possibilities for analyses of high-throughput data. The plug-in based architecture (Eclipse run time from IBM is used) allows to add new functionality using plug-ins. |
BioUML consists of 3 parts: | BioUML consists of 3 parts: | ||
* [[BioUML server]] - provides access to data and analyses methods installed on the server side for BioUML clients (workbench and web edition) via the Internet. | * [[BioUML server]] - provides access to data and analyses methods installed on the server side for BioUML clients (workbench and web edition) via the Internet. | ||
* [[BioUML workbench]] - Java application that can work standalone or as "thick" client for BioUML server. | * [[BioUML workbench]] - Java application that can work standalone or as "thick" client for BioUML server. | ||
| − | * [[BioUML web edition]] - "thin" client for BioUML server (you just need to start web browser) that provides most of functionality of BioUML workbench. It uses | + | * [[BioUML web edition]] - "thin" client for BioUML server (you just need to start web browser) that provides most of functionality of BioUML workbench. It uses [http://en.wikipedia.org/wiki/Ajax_(programming) AJAX] and [http://en.wikipedia.org/wiki/Canvas_element HTML5 <canvas>] technology for visual modeling and interactive data editing. |
| − | The developers hope that BioUML will contribute to creation of the personalized virtual physiological human or | + | The developers hope that BioUML will contribute to creation of the personalized virtual physiological human or [http://en.wikipedia.org/wiki/Virtual_patient virtual patient], which would be extremely useful in medicine as a means of computational identification of the most effective therapeutic interventions and for prediction of potential outcomes of intended treatments for a given patient. |
Revision as of 13:58, 12 April 2013
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BioUML is an open source integrated Java platform for analysis of data from omics sciences research and other advanced computational biology, for building the virtual cell and the virtual physiological human. It spans a comprehensive range of capabilities, including access to databases with experimental data, tools for formalized description of biological systems structure and functioning, as well as tools for their visualization, simulation, parameters fitting and analyses. Due to scripts (R, JavaScript) and workflow support it provides powerful possibilities for analyses of high-throughput data. The plug-in based architecture (Eclipse run time from IBM is used) allows to add new functionality using plug-ins.
BioUML consists of 3 parts:
- BioUML server - provides access to data and analyses methods installed on the server side for BioUML clients (workbench and web edition) via the Internet.
- BioUML workbench - Java application that can work standalone or as "thick" client for BioUML server.
- BioUML web edition - "thin" client for BioUML server (you just need to start web browser) that provides most of functionality of BioUML workbench. It uses AJAX and HTML5 <canvas> technology for visual modeling and interactive data editing.
The developers hope that BioUML will contribute to creation of the personalized virtual physiological human or virtual patient, which would be extremely useful in medicine as a means of computational identification of the most effective therapeutic interventions and for prediction of potential outcomes of intended treatments for a given patient.
