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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Henrichs Sensors22 22-1.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:Can a byte improve our bite? An analysis of digital twins in the food industry|Can a byte improve our bite? An analysis of digital twins in the food industry]]"'''
'''"[[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 />


The food industry faces many challenges, including the need to feed a growing population, manage food loss and waste, and improve inefficient production systems. To cope with those challenges, [[digital twin]]s—digital representations of physical entities created by integrating real-time and real-world data—seem to be a promising approach. This paper aims to provide an overview of digital twin applications in the food industry and analyze their challenges and potentials. First, a literature review is executed to examine digital twin applications in the food supply chain. The applications found are classified according to a taxonomy, and key elements to implement digital twins are identified. Further, the challenges and potentials of digital twin applications in the food industry are discussed. This survey reveals that  application of digital twins mainly target the production (i.e., agriculture) or food processing stages ... ('''[[Journal:Can a byte improve our bite? An analysis of digital twins in the food industry|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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