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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Molecular diagnostics qia symphony.jpg|140px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
The biological and ''[[life sciences industry]]'' is concerned with many aspects of physiological and medical sciences, covering the entire range of plants, bacteria, and animals. As such, there are significant crossover opportunities, such as between fermentation based companies such as beer producers and genetically engineered protein pharmaceutical companies, or between genetic engineering and biofuels. Several types of activities can be grouped under the heading of life sciences, including biorepositories, molecular diagnostics, and pharmaceutical research.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Biorepositories, as their name implies, are essentially libraries of biological specimens. Frequently, biorepositories are focused on cancer research, as the type and variety of cancers require a significant bank of available tumor, tissue, and body fluid samples. Within the U.S. the National Cancer Institute (NCI) has established the Office of Biorepositories and Biospecimen research(OBBR), whose main objective is "developing a common biorepository infrastructure that promotes resource sharing and team science, in order to facilitate multi-institutional, high throughput genomic and proteomic studies." ('''[[Life sciences 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...)

Recently featured: