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

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A '''[[data center]]''' is a facility used to house computer systems and associated components such as telecommunications and storage systems. A data center generally includes redundant or backup power supplies, redundant data communications connections, environmental controls (e.g. air conditioning and fire suppression), and various security devices. Data centers vary in size, with some large data centers capable of using as much electricity as a "medium-size town."
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


The main purpose of many data centers is for running applications that handle the core business and operational data of one or more organizations. Often those applications will be composed of multiple hosts, each running a single component. Common components of such applications include databases, file servers, application servers, and middleware. Such systems may be proprietary and developed internally by the organization or bought from enterprise software vendors. However, a data center may also solely be concerned with operations architecture or other services. ('''[[Data center|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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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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