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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Liscouski AppInfoSciWork21.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''"[[LII:The Application of Informatics to Scientific Work: Laboratory Informatics for Newbies|The Application of Informatics to Scientific Work: Laboratory Informatics for Newbies]]"'''
'''"[[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 purpose of this piece is to introduce people who are not intimately familiar with [[laboratory]] work to the basics of laboratory operations and the role that [[Informatics (academic field)|informatics]] can play in assisting scientists, engineers, and technicians in their efforts. The concepts are important because they provide a functional foundation for understanding lab work and how that work is done in the early part of the twenty-first century (things will change, just wait for it). This material is intended for anyone who is interested in seeing how modern informatics tools can help those doing scientific work. It will provide an orientation to scientific and laboratory work, as well as the systems that have been developed to make that work more productive. ('''[[LII:The Application of Informatics to Scientific Work: Laboratory Informatics for Newbies|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...)

Recently featured: