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MIC prediction specifications


Unique identifier OMICS_31475
Name MIC prediction
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python, Shell (Bash)
Computer skills Advanced
Stability Stable
KMC, XGBoost
Maintained Yes




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  • person_outline James Davis

Publication for MIC prediction

MIC prediction citation


Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae

Sci Rep
PMCID: 5765115
PMID: 29323230
DOI: 10.1038/s41598-017-18972-w
call_split See protocol

[…] high value of 1 (1 is the default and maximum value allowed for XGBoost) were chosen for evaluation.The accuracy of the XGBoost model was evaluated in two ways. First, the accuracy of each individual MIC prediction over the test set was assessed within ±1 two-fold dilution factor. Secondly the coefficient of determination, or R2, was also used as a metric during the hyperparameter tuning.A 2k fact […]

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MIC prediction institution(s)
University of Chicago Consortium for Advanced Science and Engineering, Chicago, IL, USA; Houston Methodist Research Inst and Houston Methodist Hospital, Houston, TX, USA; Food and Drug Admin, Center for Veterinary Med, Office of Research, Laurel, MD, USA; Computing, Environnement and Life Sciences, Argonne National Lab, Argonne, IL, USA; University of Chicago, Department of Computer Science, Chicago, IL, USA; Food and Drug Admin, Center for Veterinary Medicine, Office of Research, Laurel, MD, USA
MIC prediction funding source(s)
Supported by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Service [Contract No. HHSN272201400027C].

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