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A '''[[biobank]]''' is a collection of biological samples (usually human) for use in research. The samples may also include personal medical and genealogical data. Sites for these collections come in different forms, typically based on the types of samples being stored and the scientific domain associated with them. These sites can be loosely categorized into two types: those based on biological specimens from patients and donors, and those specifically designed to aid in population-based research.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Biobanks give researchers access to data representing larger numbers of people than could be analyzed in previously used systems. Furthermore, samples in biobanks and the data derived from those samples can often be used by multiple researchers for multiple purposes. Large collections of samples representing tens or hundreds of thousands of individuals are necessary to conduct certain studies. However, these activities come with their share of questions regarding research and medical ethics, and they have provoked discussions in some community circles. While viewpoints on what constitutes appropriate biobank ethics diverge, consensus has been reached that relying on biobanks without carefully considered governing principles and policies could negatively impact communities participating in biobank programs. ('''[[Biobank|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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