Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1.1 Davis FrontBioinfo2022 40.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Signoroni NatComm23 14.png|240px]]</div>
'''"[[Journal:ApE, A Plasmid Editor: A freely available DNA manipulation and visualization program|ApE, A Plasmid Editor: A freely available DNA manipulation and visualization program]]"'''
'''"[[Journal:Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology|Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology]]"'''


A Plasmid Editor (ApE) is a free, multi-platform application for [[Data visualization|visualizing]], designing, and presenting biologically relevant [[DNA sequencing|DNA sequences]]. ApE provides a flexible framework for annotating a sequence manually or using a user-defined library of features. ApE can be used in designing [[plasmid]]s and other constructs via ''in silico'' simulation of cloning methods such as [[polymerase chain reaction]] (PCR), Gibson assembly, restriction-ligation assembly, and Golden Gate assembly. In addition, ApE provides a platform for creating visually appealing linear and circular plasmid maps. It is available for Mac, PC, and Linux-based platforms and can be downloaded at https://jorgensen.biology.utah.edu/wayned/ape/. ('''[[Journal:ApE, A Plasmid Editor: A freely available DNA manipulation and visualization program|Full article...]]''')<br />
Full [[laboratory automation]] is revolutionizing work habits in an increasing number of clinical [[microbiology]] facilities worldwide, generating huge streams of [[Imaging|digital images]] for interpretation. Contextually, [[deep learning]] (DL) architectures are leading to paradigm shifts in the way computers can assist with difficult visual interpretation tasks in several domains. At the crossroads of these epochal trends, we present a system able to tackle a core task in clinical microbiology, namely the global interpretation of diagnostic [[Bacteria|bacterial]] [[Cell culture|culture]] plates, including presumptive [[pathogen]] identification. This is achieved by decomposing the problem into a hierarchy of complex subtasks and addressing them with a multi-network architecture we call DeepColony ... ('''[[Journal:Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology|Full article...]]''')<br />
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Latest revision as of 15:02, 3 June 2024

Fig1 Signoroni NatComm23 14.png

"Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology"

Full laboratory automation is revolutionizing work habits in an increasing number of clinical microbiology facilities worldwide, generating huge streams of digital images for interpretation. Contextually, deep learning (DL) architectures are leading to paradigm shifts in the way computers can assist with difficult visual interpretation tasks in several domains. At the crossroads of these epochal trends, we present a system able to tackle a core task in clinical microbiology, namely the global interpretation of diagnostic bacterial culture plates, including presumptive pathogen identification. This is achieved by decomposing the problem into a hierarchy of complex subtasks and addressing them with a multi-network architecture we call DeepColony ... (Full article...)
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