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Bioinformatics Analysis of Protein Secretion in Plants

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Plant Protein Secretion

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1662))

Abstract

In sessile plants, the dynamic protein secretion pathways orchestrate the cellular responses to internal signals and external environmental changes in almost every aspect of plant developmental events. The cohort of plant proteins, secreted from the plant cells into the extracellular matrix, has been annotated as plant secretome. Therefore, the identification and characterization of secreted proteins will discover novel secretory potentials and establish the functional connection between cellular protein secretion and plant physiological phenomena. Noteworthy, an increasing number of bioinformatics databases and tools have been developed for computational predictions on either secreted proteins or secretory pathways. This chapter summarizes current accessible databases and tools for protein secretion analysis in Arabidopsis thaliana and higher plants, and provides feasible methodologies for bioinformatics analysis of secretome studies for the plant research community.

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Acknowledgments

The author would like to thank Hong Kong RCG-GRF Grant (No. CUHK14104716) and The Chinese University of Hong Kong Research Committee Direct Grant (No.4053143) to L.C.

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Authors and Affiliations

  1. RGC-AoE Centre for Organelle Biogenesis and Function, School of Life Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Liyuan Chen

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  1. Liyuan Chen
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Correspondence to Liyuan Chen .

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Editors and Affiliations

  1. School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China

    Liwen Jiang

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Chen, L. (2017). Bioinformatics Analysis of Protein Secretion in Plants. In: Jiang, L. (eds) Plant Protein Secretion. Methods in Molecular Biology, vol 1662. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7262-3_3

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  • DOI: https://doi.org/10.1007/978-1-4939-7262-3_3

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7261-6

  • Online ISBN: 978-1-4939-7262-3

  • eBook Packages: Springer Protocols

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