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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig6 Ogle FrontBigData2021 4.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''"[[Journal:Named data networking for genomics data management and integrated workflows|Named data networking for genomics data management and integrated workflows]]"'''
'''"[[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 />


Advanced [[Imaging informatics|imaging]] and [[DNA sequencing]] technologies now enable the diverse biology community to routinely generate and analyze terabytes of high-resolution biological data. The community is rapidly heading toward the petascale in single-investigator [[laboratory]] settings. As evidence, the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) central DNA sequence repository alone contains over 45 petabytes of biological data. Given the geometric growth of this and other [[genomics]] repositories, an exabyte of mineable biological data is imminent. The challenges of effectively utilizing these datasets are enormous, as they are not only large in size but also stored in various geographically distributed repositories such as those hosted by the NCBI, as well as in the DNA Data Bank of Japan (DDBJ), European Bioinformatics Institute (EBI), and NASA’s GeneLab. ('''[[Journal:Named data networking for genomics data management and integrated workflows|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...)

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