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'''"[[Journal:Implementing an institution-wide electronic laboratory notebook initiative|Implementing an institution-wide electronic laboratory notebook initiative]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|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 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 />


To strengthen institutional research [[Information management|data management]] practices, the [[Indiana University – Purdue University Indianapolis|Indiana University School of Medicine]] (IUSM) licensed an [[electronic laboratory notebook]] (ELN) to improve the organization, security, and shareability of [[information]] and data generated by the school’s researchers. The Ruth Lilly Medical Library led implementation on behalf of the IUSM’s Office of Research Affairs. This article describes the pilot and full-scale implementation of an ELN at IUSM. The initial pilot of the ELN in late 2018 involved 15 research labs, with access expanded in 2019 to all academic medical school constituents ... ('''[[Journal:Implementing an institution-wide electronic laboratory notebook initiative|Full article...]]''')<br />
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Latest 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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