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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Day 253 - West Midlands Police - Forensic Science Lab (7969822920).jpg|240px]]</div>
<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]]"'''
'''"[[Journal:The need for informatics to support forensic pathology and death investigation|The need for informatics to support forensic pathology and death investigation]]"'''


As a result of their practice of medicine, [[Forensic science|forensic]] pathologists create a wealth of data regarding the causes of and reasons for sudden, unexpected or violent deaths. This data have been effectively used to protect the health and safety of the general public in a variety of ways despite current and historical limitations. These limitations include the lack of data standards between the thousands of death investigation (DI) systems in the United States, rudimentary electronic information systems for DI, and the lack of effective communications and interfaces between these systems. Collaboration between forensic pathology and [[health informatics|clinical informatics]] is required to address these shortcomings and a path forward has been proposed that will enable forensic pathology to maximize its effectiveness by providing timely and actionable [[information]] to public health and public safety agencies. ('''[[Journal:The need for informatics to support forensic pathology and death investigation|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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