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The '''[[National Institute for Occupational Safety and Health]]''' ('''NIOSH''') is the U.S. Federal agency responsible for conducting research and making recommendations for the prevention of work-related injury and illness. NIOSH is part of the [[Centers for Disease Control and Prevention]] (CDC) within the [[United States Department of Health and Human Services|U.S. Department of Health and Human Services]]. NIOSH provides national and world leadership to prevent work-related illness, injury, disability, and death by gathering information, conducting scientific research, and translating the knowledge gained into products and services.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


NIOSH is headquartered in Washington, D.C., with research laboratories and offices in Cincinnati, Ohio; Morgantown, West Virginia; Pittsburgh, Pennsylvania; Denver, Colorado; Anchorage, Alaska; Spokane, Washington; and Atlanta, Georgia. NIOSH is a professionally diverse organization with a staff ceiling of over 1,400 (as of 2005; operating with about 1,300 full-time employees) people representing a wide range of disciplines including epidemiology, medicine, industrial hygiene, safety, psychology, engineering, chemistry, and statistics. NIOSH was established to help ensure safe and healthful working conditions by providing research, information, education, and training in the field of occupational safety and health. ('''[[National Institute for Occupational Safety and Health|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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