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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Yoon LabAniRes22 38.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''"[[Journal:Laboratory information management system for COVID-19 non-clinical efficacy trial data|Laboratory information management system for COVID-19 non-clinical efficacy trial data]]"'''
'''"[[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 />


As the number of large-scale research studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable data format is needed. For example, in response to the [[coronavirus disease 2019]] (COVID-19) [[pandemic]], a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. In this study, a [[laboratory information management system]] (LIMS) has been adopted to systemically manage, via web interface, various COVID-19 non-clinical trial data—including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multi-organ [[histopathology]]—from multiple institutions ... ('''[[Journal:Laboratory information management system for COVID-19 non-clinical efficacy trial data|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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