Biolog Phenotype MicroArray
     Serious Technology for Serious Microbiology March 2014
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Useful Links

Leveraging Genomic Data with Phenomic Data

Phenotype MicroArray
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New publications illustrate the application of Phenotype MicroArray (PM) technology in virulence research. In this newsletter, we present three papers from the primary literature illustrating successful use of PM technology to further understand mechanisms of virulence and host cell-pathogen interaction.
 
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  DuctApe: A Suite for the Analysis and Correlation of Genomic and OmniLog™ Phenotype MicroArray Data
The authors present a software suite that integrates the analysis of both DNA and Phenotype MicroArray data. In addition to the introduction of the AV index for PM data, a novel representation of PM data called a ring diagram is presented. These genomic and phenomic tools facillitate the correlation of phenotypic variability with genomic variation. The analysis can be performed on single strains, pairs of strains, or groups of strains.
 
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  OPM: An R Package for Analysing OmniLog® Phenotype MicroArray Data
The publication features software for the analysis of Phenotype MicroArray data using the free statistical computing platform known as R. The software facilitates storage of metadata, graphic representation of PM data, statistical estimation of kinetic parameters, and machine learning methods for identifying pathways of high phenotypic variability.
 
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  Metabolic Model Refinement Using Phenotypic Microarray Data
The paper offers a protocol for refinement of in silico metabolic models by PM data using both manual and algorithmic approaches. Decision trees lead to model refinement or plausible explanations of inconsistencies between PM and model data. Model refinements include addition of transporters, addition of pathways, removal of reactions, and others.
 
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Phenotype MicroArray Technology
Biolog's Phentoype MicroArray technology enables researchers to evaluate nearly 2000 phenotypes of a microbial cell in a single experiment. This integrated system of cellular assays, instrumentation and bioinformatics software provides cellular knowledge that complements molecular information, helping you interpret and find the relevant aspects in massive amounts of gene expression or proteomics data. Through comprehensive and precise quantitation of phenotypes, researchers are able to obtain an unbiased perspective of the effect on cells of genetic differences, environmental change, exposure to chemicals or drugs, and more.
 
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