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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab1 Kyobe BiopresBiobank2017 15-2.png|240px]]</div>
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'''"[[Journal:Selecting a laboratory information management system for biorepositories in low- and middle-income countries: The H3Africa experience and lessons learned|Selecting a laboratory information management system for biorepositories in low- and middle-income countries: The H3Africa experience and lessons learned]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Biorepositories in Africa need significant infrastructural support to meet International Society for Biological and Environmental Repositories (ISBER) Best Practices to support population-based genomics research. ISBER recommends a biorepository information management system which can manage workflows from biospecimen receipt to distribution. The H3Africa Initiative set out to develop regional African biorepositories where Uganda, Nigeria, and South Africa were successfully awarded grants to develop the state-of-the-art biorepositories. The biorepositories carried out an elaborate process to evaluate and choose a [[laboratory information management system]] (LIMS) with the aim of integrating the three geographically distinct sites. In this article, we review the processes, African experience, and lessons learned, and we make recommendations for choosing a biorepository LIMS in the African context. ('''[[Selecting a laboratory information management system for biorepositories in low- and middle-income countries: The H3Africa experience and lessons learned|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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