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:Where the Trees Are - NASA Earth Observatory.jpg|180px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''[[Forest informatics]]''' is a multidisciplinary field of science that "harnesses the power of computational and information technologies to organize and analyze biological data from research collections, experiments, remote sensing, modeling, database searches and instrumentation and deliver them to users throughout the world." Computational and information management technologies used to support decision-making activities in the field of forest informatics include decision support systems, mathematical modeling software, statistical and algorithmic analysis tools, geographic information systems, global positioning systems, and shared databases.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Forestry informatics can help tackle problems and tasks such as optimizing harvest scheduling and crew assignment, computing wildfire risk indices, assessing forestry management guidelines, resolving log bucking problems, and developing and optimizing mathematical algorithms for ecological modeling. ('''[[Forest informatics|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'': [[International Electrotechnical Commission]], [[Physician office laboratory]], [[United States Department of Health and Human Services]]
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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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