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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Mackert JournalOfMedIntRes2016 18-10.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''"[[Journal:Health literacy and health information technology adoption: The potential for a new digital divide|Health literacy and health information technology adoption: The potential for a new digital divide]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Approximately one-half of American adults exhibit low health literacy and thus struggle to find and use [[Health informatics|health information]]. Low health literacy is associated with negative outcomes, including overall poorer health. [[Health information technology]] (HIT) makes health information available directly to patients through electronic tools including [[patient portal]]s, wearable technology, and mobile apps. The direct availability of this [[information]] to patients, however, may be complicated by misunderstanding of HIT privacy and information sharing. The purpose of this study was to determine whether health literacy is associated with patients’ use of four types of HIT tools: fitness and nutrition apps, activity trackers, and patient portals. ('''[[Journal:Health literacy and health information technology adoption: The potential for a new digital divide|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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