ArticleBMC bioinformatics2016
A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Immunoglobulin G N-glycan Biomarkers for Autoimmune Diseases: Current State and a Glycoinformatics Perspective.International journal of molecular sciences · 2022Review
- Correcting for sparsity and interdependence in glycomics by accounting for glycan biosynthesis.Nature communications · 2021Article
- Big-Data Glycomics: Tools to Connect Glycan Biosynthesis to Extracellular Communication.Trends in biochemical sciences · 2021Review
- N-Glycosylation Network Construction and Analysis to Modify Glycans on the Spike (S) Glycoprotein of SARS-CoV-2.Frontiers in bioinformatics · 2021Article
- A Markov model of glycosylation elucidates isozyme specificity and glycosyltransferase interactions for glycoengineering.Current research in biotechnology · 2020Article
- A consensus-based and readable extension ofBeilstein journal of organic chemistry · 2020Article
- Identification of LCA-binding Glycans as a Novel Biomarker for Esophageal Cancer Metastasis using a Lectin Array-based Strategy.Journal of Cancer · 2020Article
- What can mathematical modelling say about CHO metabolism and protein glycosylation?Computational and structural biotechnology journal · 2017Review
- Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAbnormalities in glycan biosynthesis have been conclusively related to various diseases, whereas the complexity of the glycosylation process has impeded the quantitative analysis of biochemical experimental data for the identification of glycoforms contributing to disease. To overcome this limitation, the automatic construction of glycosylation reaction networks in silico is a critical step.
resultsIn this paper, a framework K2014 is developed to automatically construct N-glycosylation networks in MATLAB with the involvement of the 27 most-known enzyme reaction rules of 22 enzymes, as an extension of previous model KB2005. A toolbox named Glycosylation Network Analysis Toolbox (GNAT) is applied to define network properties systematically, including linkages, stereochemical specificity and reaction conditions of enzymes. Our network shows a strong ability to predict a wider range of glycans produced by the enzymes encountered in the Golgi Apparatus in human cell expression systems.
conclusionsOur results demonstrate a better understanding of the underlying glycosylation process and the potential of systems glycobiology tools for analyzing conventional biochemical or mass spectrometry-based experimental data quantitatively in a more realistic and practical way.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.