Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Desktop-as-a-Service in Cloud Computing architectures.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''[[Desktop virtualization]]''' is software technology that separates the desktop environment and associated application software from the physical client device that is used to access it.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Desktop virtualization can be used in conjunction with application virtualization and user profile management systems (known as "user virtualization") to provide a comprehensive desktop environment management system. In this mode, all the components of the desktop are virtualized, which allows for a highly flexible and much more secure desktop delivery model. In addition, this approach supports a more complete desktop disaster recovery strategy as all components are essentially saved in the [[data center]] and backed up through traditional redundant maintenance systems. If a user's device or hardware is lost, the restore is much more straightforward and simple; all the components will be present at log-in from another device.  Additionally, because no data is saved to the user's device, chances are low any critical data can be retrieved and compromised if the device is lost. ('''[[Desktop virtualization|Full article...]]''')<br />
[[Information]] is the cornerstone of [[research]], from experimental data/[[metadata]] and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging [[laboratory information management system]]s (LIMS) to transform this large information load into useful scientific findings. The development of [[mathematical model]]s that can predict the properties of biological systems is the holy grail of [[computational biology]]. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... ('''[[Journal:Ten simple rules for managing laboratory information|Full article...]]''')<br />
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''Recently featured'': [[Comprehensive outpatient rehabilitation facility]], [[National Institutes of Health]], [[Laboratory information system]]
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Latest revision as of 18:03, 10 June 2024

Fig2 Berezin PLoSCompBio23 19-12.png

"Ten simple rules for managing laboratory information"

Information is the cornerstone of research, from experimental data/metadata and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems (LIMS) to transform this large information load into useful scientific findings. The development of mathematical models that can predict the properties of biological systems is the holy grail of computational biology. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... (Full article...)

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