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Multi –omics and metabolic modelling pipelines: challenges and tools for systems microbiology

Marco Fondi, Pietro Liò
doi: https://doi.org/10.1101/013532
Marco Fondi
1Computational Biology group (ComBo), University of Florence, Via Madonna del Piano 6, Sesto Fiorentino, Florence, 50019, Italy
2Laboratory of Microbial and Molecular Evolution, Department of Biology, University of Florence, Via Madonna del Piano 6, Sesto Fiorentino, Florence, 50019, Italy.
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  • For correspondence: marco.fondi@unifi.it
Pietro Liò
3University of Cambridge, Computer Laboratory, 15 JJ Thomson Avenue, CB3 0FD Cambridge, UK
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Abstract

Integrated -omics approaches are quickly spreading across microbiology research labs, leading to i) the possibility of detecting previously hidden features of microbial cells like multi-scale spatial organisation and ii) tracing molecular components across multiple cellular functional states. This promises to reduce the knowledge gap between genotype and phenotype and poses new challenges for computational microbiologists. We underline how the capability to unravel the complexity of microbial life will strongly depend on the integration of the huge and diverse amount of information that can be derived today from - omics experiments. In this work, we present opportunities and challenges of multi –omics data integration in current systems biology pipelines. We here discuss which layers of biological information are important for biotechnological and clinical purposes, with a special focus on bacterial metabolism and modelling procedures. A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted January 07, 2015.
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Multi –omics and metabolic modelling pipelines: challenges and tools for systems microbiology
Marco Fondi, Pietro Liò
bioRxiv 013532; doi: https://doi.org/10.1101/013532
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Multi –omics and metabolic modelling pipelines: challenges and tools for systems microbiology
Marco Fondi, Pietro Liò
bioRxiv 013532; doi: https://doi.org/10.1101/013532

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