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Optimization of multi-omic genome-scale models: Methodologies, hands-on tutorial, and perspectives

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Publication date2018
Host publicationMetabolic Network Reconstruction and Modeling: Methods and Protocols
EditorsMarco Fondi
Place of PublicationNew York, NY
PublisherHumana Press
Number of pages19
ISBN (electronic)9781493975280
ISBN (print)9781493975273, 9781493985111
<mark>Original language</mark>English

Publication series

NameMethods in Molecular Biology
PublisherHumana Press
ISSN (Print)1064-3745
ISSN (electronic)1940-6029

Abstract

Genome-scale metabolic models are valuable tools for assessing the
metabolic potential of living organisms. Being downstream of gene expression,
metabolism is being increasingly used as an indicator of the phenotypic outcome
for drugs and therapies. We here present a review of the principal methods used for constraint-based modelling in systems biology, and explore how the integration of multi-omic data can be used to improve phenotypic predictions of genome-scale metabolic models. We believe that the large-scale comparison of the metabolic response of an organism to different environmental conditions will be an important challenge for genome-scale models. Therefore, within the context of multi-omic methods, we describe a tutorial for multi-objective optimisation using the metabolic and transcriptomics adaptation estimator (METRADE), implemented in MATLAB. METRADE uses microarray and codon usage data to model bacterial metabolic response to environmental conditions (e.g. antibiotics, temperatures, heat shock). Finally, we discuss key considerations for the integration of multi-omic networks into metabolic models, towards automatically extracting knowledge from such models.