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Protein Secretion Prediction Tools and Extracellular Vesicles Databases

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Proteomics Data Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2361))

Abstract

Secreted proteins play important roles in several biological processes such as growth, proliferation differentiation, cell-cell communication, migration, and apoptosis; moreover, these extracellular molecules mediate homeostasis by influencing the cross-talking within the surrounding tissues. Currently, the research area of cell secretome has become of great interest since the profiling of secreted proteins could be essential for the biomarker discovery and for the identification of new therapeutic strategies. Several bioinformatic platforms have been implemented for the in silico characterization of secreted proteins: this chapter describes a typical workflow for the analysis of proteins secreted by cultured cells through bioinformatic approaches. Central issue is related to discrimination between proteins secreted by classical and non-classical pathways. Therefore, specific prediction tools for the classification of candidate secreted proteins are here presented.

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Authors and Affiliations

  1. Department of Biotechnology, University of Verona, Verona, Italy

    Daniela Cecconi, Claudia Di Carlo & Jessica Brandi

Authors
  1. Daniela Cecconi
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  2. Claudia Di Carlo
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  3. Jessica Brandi
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Corresponding author

Correspondence to Jessica Brandi .

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Editors and Affiliations

  1. Department of Biotechnology, University of Verona, VERONA, Verona, Italy

    Daniela Cecconi

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© 2021 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Cecconi, D., Di Carlo, C., Brandi, J. (2021). Protein Secretion Prediction Tools and Extracellular Vesicles Databases. In: Cecconi, D. (eds) Proteomics Data Analysis. Methods in Molecular Biology, vol 2361. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1641-3_13

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  • DOI: https://doi.org/10.1007/978-1-0716-1641-3_13

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1640-6

  • Online ISBN: 978-1-0716-1641-3

  • eBook Packages: Springer Protocols

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