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Plant Membrane Proteomics

Overview of attention for book
Plant Membrane Proteomics
Humana Press, New York, NY

Table of Contents

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    Book Overview
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    Chapter 1 Free Flow Zonal Electrophoresis for Fractionation of Plant Membrane Compartments Prior to Proteomic Analysis
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    Chapter 2 Isolation and Purity Assessment of Membranes from Norway Spruce
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    Chapter 3 Nuclear Proteome: Isolation of Intact Nuclei, Extraction of Nuclear Proteins, and 2-DE Analysis
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    Chapter 4 Identification of Plant Nuclear Proteins Based on a Combination of Flow Sorting, SDS-PAGE, and LC-MS/MS Analysis
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    Chapter 5 Isolation, Purity Assessment, and Proteomic Analysis of Nuclei
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    Chapter 6 Proteomic Analysis of Rice Golgi Membranes Isolated by Floating Through Discontinuous Sucrose Density Gradient
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    Chapter 7 Analyzing the Vacuolar Membrane (Tonoplast) Proteome
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    Chapter 8 Preparation of Membrane Fractions (Envelope, Thylakoids, Grana, and Stroma Lamellae) from Arabidopsis Chloroplasts for Quantitative Proteomic Investigations and Other Studies
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    Chapter 9 Isolation of Intact Thylakoid Membranes from Heterocysts of Filamentous, Nitrogen-Fixing Cyanobacteria
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    Chapter 10 Targeted Quantification of Isoforms of a Thylakoid-Bound Protein: MRM Method Development
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    Chapter 11 Sample Preparation for Analysis of the Plant Mitochondrial Membrane Proteome
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    Chapter 12 Plasma Membrane Proteomics of Arabidopsis Suspension-Cultured Cells Associated with Growth Phase Using Nano-LC-MS/MS
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    Chapter 13 Mini-Scale Isolation and Preparation of Plasma Membrane Proteins from Potato Roots for LC/MS Analysis
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    Chapter 14 Assay of Plasma Membrane H+-ATPase in Plant Tissues under Abiotic Stresses
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    Chapter 15 Absolute Quantitation of In Vitro Expressed Plant Membrane Proteins by Targeted Proteomics (MRM) for the Determination of Kinetic Parameters
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    Chapter 16 MSE for Label-Free Absolute Protein Quantification in Complex Proteomes
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    Chapter 17 Identification and Characterization of Plant Membrane Proteins Using ARAMEMNON
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    Chapter 18 VANTED: A Tool for Integrative Visualization and Analysis of -Omics Data
Attention for Chapter 17: Identification and Characterization of Plant Membrane Proteins Using ARAMEMNON
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Chapter title
Identification and Characterization of Plant Membrane Proteins Using ARAMEMNON
Chapter number 17
Book title
Plant Membrane Proteomics
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7411-5_17
Pubmed ID
29086409
Book ISBNs
978-1-4939-7409-2, 978-1-4939-7411-5
Authors

Rainer Schwacke, Ulf-Ingo Flügge

Abstract

Membrane proteins are estimated to constitute a quarter of all proteins encoded in plant genomes, yet only a limited number have been experimentally characterized. This is mainly due to the large variation in particular physical properties coupled with purification difficulties. Computational methods are therefore very helpful for the initial characterization of a candidate membrane protein. Individual prediction tools can, with varying levels of success, predict the occurrence of transmembrane spans, the subcellular location, and lipid posttranslational modifications. Since it can be tedious to consult each prediction tool separately, ARAMEMNON has been designed to compile various computational predictions for plant membrane proteins and to present the results via a user-friendly web interface. This protocol describes how to use ARAMEMNON to identify and characterize plant membrane proteins.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 20%
Student > Postgraduate 2 13%
Student > Master 2 13%
Librarian 1 7%
Student > Bachelor 1 7%
Other 3 20%
Unknown 3 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 40%
Agricultural and Biological Sciences 2 13%
Computer Science 2 13%
Unspecified 1 7%
Unknown 4 27%

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