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'''"[[Journal:Electronic laboratory notebooks in a public–private partnership|Electronic laboratory notebooks in a public–private partnership]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


This report shares the experience during selection, implementation and maintenance phases of an [[electronic laboratory notebook]] (ELN) in a public–private partnership project and comments on users' feedback. In particular, we address which time constraints for roll-out of an ELN exist in granted projects and which benefits and/or restrictions come with out-of-the-box solutions. We discuss several options for the implementation of support functions and potential advantages of open-access solutions. Connected to that, we identified willingness and a vivid culture of data sharing as the major item leading to success or failure of collaborative research activities. The feedback from users turned out to be the only angle for driving technical improvements, but also exhibited high efficiency. Based on these experiences, we describe best practices for future projects on implementation and support of an ELN supporting a diverse, multidisciplinary user group based in academia, NGOs, and/or for-profit corporations located in multiple time zones. ('''[[Journal:Electronic laboratory notebooks in a public–private partnership|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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