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The [[chemical industry]] is comprised of numerous sectors, with no fewer than 45 different subdivisions, including glass manufacturing, petrochemical manufacturing, electronics chemicals, ceramics, and dye and pigment manufacturing to name a few.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Glass manufacturing is a process that is largely dependent on raw material quality control, as in process controls are limited by the fact that the process for manufacturing glass is high temperature, and does not lend itself to any sort of sampling process. That being said, temperature is actually a key control measure, and multivariate process control methods have been developed to maximize finished product quality. Primary petrochemicals such as ethylene, methanol, and benzene are used to produce a variety of intermediate and derivative products which ultimately are used to produce an amazing array of materials of great importance to the modern industrial world, such as plastics, tires, solvents, and the like. ('''[[Chemical industry|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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