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'''"[[Journal:ISO 15189 accreditation: Navigation between quality management and patient safety|ISO 15189 accreditation: Navigation between quality management and patient safety]]"'''
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Accreditation is a valuable resource for [[Clinical laboratory|clinical laboratories]], and the development of an international standard for their accreditation represented a milestone on the path towards improved quality and safety in [[laboratory]] medicine. The recent revision of the international standard, [[ISO 15189]], has further strengthened its value not only for improving the [[Quality management system|quality system]] of a clinical laboratory but also for better answering the request for competence, focus on customers’ needs and ultimate value of laboratory services. Although in some countries more general standards such as [[ISO 9000|ISO 9001]] for quality systems or [[ISO 17025]] for testing laboratories are still used, there is increasing recognition of the value of ISO 15189 as the most appropriate and useful standard for the accreditation of medical laboratories. In fact, only this international standard recognizes the importance of all steps of the total testing process, namely extra-analytical phases, the need to focus on technical competence in addition to quality systems, and the focus on customers’ needs. ('''[[Journal:ISO 15189 accreditation: Navigation between quality management and patient safety|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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