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WIREs Syst Biol Med
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Integration of systems glycobiology with bioinformatics toolboxes, glycoinformatics resources, and glycoproteomics data

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The glycome constitutes the entire complement of free carbohydrates and glycoconjugates expressed on whole cells or tissues. ‘Systems Glycobiology’ is an emerging discipline that aims to quantitatively describe and analyse the glycome. Here, instead of developing a detailed understanding of single biochemical processes, a combination of computational and experimental tools are used to seek an integrated or ‘systems‐level’ view. This can explain how multiple biochemical reactions and transport processes interact with each other to control glycome biosynthesis and function. Computational methods in this field commonly build in silico reaction network models to describe experimental data derived from structural studies that measure cell‐surface glycan distribution. While considerable progress has been made, several challenges remain due to the complex and heterogeneous nature of this post‐translational modification. First, for the in silico models to be standardized and shared among laboratories, it is necessary to integrate glycan structure information and glycosylation‐related enzyme definitions into the mathematical models. Second, as glycoinformatics resources grow, it would be attractive to utilize ‘Big Data’ stored in these repositories for model construction and validation. Third, while the technology for profiling the glycome at the whole‐cell level has been standardized, there is a need to integrate mass spectrometry derived site‐specific glycosylation data into the models. The current review discusses progress that is being made to resolve the above bottlenecks. The focus is on how computational models can bridge the gap between ‘data’ generated in wet‐laboratory studies with ‘knowledge’ that can enhance our understanding of the glycome. WIREs Syst Biol Med 2015, 7:163–181. doi: 10.1002/wsbm.1296 This article is categorized under: Models of Systems Properties and Processes > Cellular Models Analytical and Computational Methods > Computational Methods Biological Mechanisms > Metabolism
Carbohydrate life‐cycle. Carbohydrates are processed through various biosynthetic and degradative transformations in cells.
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Visualization and modeling of glycosylation reaction networks: Synthesis of the N‐linked glycosylation pathway described by Umana and Bailey. Glycosylation reaction network presented here was visualized using the GlycanNetViewer function of GNAT. The network can be exported into an SBML file that contains all glycan sequences. The computational simulation of this network using MATLAB predicts that the extent of N‐linked glycosylation decreases upon increasing protein productivity (i.e. macroheterogeneity increases, see plot at top‐left). This affects the relative concentration of bi‐ and tri‐antennary N‐glycans.
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Automated Pathway construction. Three algorithms have been implemented in GNAT to automate network synthesis. These include the forward, reverse, and connection network inference algorithms. (Reprinted with permission from Ref )
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Representation of glycan structures. Glycan representation in linear, graphical (2D), and data exchangeable formats: (a) LINUCS, (b) IUPAC, (c) CarbBank 2D representation, (d) IUPAC graphics, (e) CFG recommended graphics, and (f) GlycoCT XML format.
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Entity‐based modeling framework. UML diagram of the classes used for the construction of glycosylation reaction networks in GNAT (http://sourceforge.net/projects/gnatmatlab/). (Modified with permission from Ref . Copyright 2013 Oxford University Press)
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Glycan repertoire. A variety of glycans with diverse structures are found in mammals. These include: (a) N‐linked glycans; (b). O‐GalNAc type O‐linked glycans; (c) O‐GlcNAcylated glycans; (d) glycosaminoglycans; (e) glycosphingolipids; (f)–(h) O‐linked glycans initiated by fucose (panel f), glucose (g), or mannose (h); and (i) C‐mannosylated glycans attached to Trp. Note that only selected examples of each glycan class are shown.
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Analytical and Computational Methods > Computational Methods
Models of Systems Properties and Processes > Cellular Models
Biological Mechanisms > Metabolism

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