A Bayesian framework for the classification of microbial gene activity states

A Bayesian framework for the classification of microbial gene activity states

Numerous methods for classifying gene activity states based on gene expression data have been proposed for use in downstream applications, such as incorporating transcriptomics data into metabolic models in order to improve resulting flux predictions. These methods often attempt to classify gene act...

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Bibliographic Details
Main Authors: Craig Disselkoen, Brian Greco, Kaitlyn Cook, Kristin Koch, Reginald Lerebours, Chase Viss, Joshua Cape, Elizabeth Held, Yonatan Ashenafi, Karen Fischer, Allyson Acosta, Mark Cunningham, Aaron A Best, Matthew DeJongh, Nathan Tintle
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-08-01
Series:Frontiers in Microbiology
Subjects:
Bacteria
Gene Expression
Metabolic Modelling
Bayesian model
Gene activity
Online Access:http://journal.frontiersin.org/Journal/10.3389/fmicb.2016.01191/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fmicb.2016.01191/full

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