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Proteomis in Systems Biology

Overview of attention for book
Cover of 'Proteomis in Systems Biology'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Multiplexed Quantitative Proteomics for High-Throughput Comprehensive Proteome Comparisons of Human Cell Lines.
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    Chapter 2 Sample Preparation Approaches for iTRAQ Labeling and Quantitative Proteomic Analyses in Systems Biology.
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    Chapter 3 Two Birds with One Stone: Parallel Quantification of Proteome and Phosphoproteome Using iTRAQ.
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    Chapter 4 Selected Reaction Monitoring to Measure Proteins of Interest in Complex Samples: A Practical Guide.
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    Chapter 5 Monitoring PPARG-Induced Changes in Glycolysis by Selected Reaction Monitoring Mass Spectrometry.
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    Chapter 6 A Targeted MRM Approach for Tempo-Spatial Proteomics Analyses.
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    Chapter 7 Targeted Phosphoproteome Analysis Using Selected/Multiple Reaction Monitoring (SRM/MRM).
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    Chapter 8 Testing Suitability of Cell Cultures for SILAC-Experiments Using SWATH-Mass Spectrometry.
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    Chapter 9 Combining Amine-Reactive Cross-Linkers and Photo-Reactive Amino Acids for 3D-Structure Analysis of Proteins and Protein Complexes.
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    Chapter 10 Tissue MALDI Mass Spectrometry Imaging (MALDI MSI) of Peptides.
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    Chapter 11 Ethyl Esterification for MALDI-MS Analysis of Protein Glycosylation.
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    Chapter 12 Characterization of Protein N-Glycosylation by Analysis of ZIC-HILIC-Enriched Intact Proteolytic Glycopeptides.
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    Chapter 13 Simple and Effective Affinity Purification Procedures for Mass Spectrometry-Based Identification of Protein-Protein Interactions in Cell Signaling Pathways.
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    Chapter 14 A Systems Approach to Understand Antigen Presentation and the Immune Response.
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    Chapter 15 Profiling of Small Molecules by Chemical Proteomics.
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    Chapter 16 Generating Sample-Specific Databases for Mass Spectrometry-Based Proteomic Analysis by Using RNA Sequencing.
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    Chapter 17 A Proteomic Workflow Using High-Throughput De Novo Sequencing Towards Complementation of Genome Information for Improved Comparative Crop Science.
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    Chapter 18 From Phosphoproteome to Modeling of Plant Signaling Pathways.
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    Chapter 19 Interpretation of Quantitative Shotgun Proteomic Data.
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    Chapter 20 A Simple Workflow for Large Scale Shotgun Glycoproteomics.
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    Chapter 21 Systemic Analysis of Regulated Functional Networks.
Attention for Chapter 17: A Proteomic Workflow Using High-Throughput De Novo Sequencing Towards Complementation of Genome Information for Improved Comparative Crop Science.
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Chapter title
A Proteomic Workflow Using High-Throughput De Novo Sequencing Towards Complementation of Genome Information for Improved Comparative Crop Science.
Chapter number 17
Book title
Proteomics in Systems Biology
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3341-9_17
Pubmed ID
26700053
Book ISBNs
978-1-4939-3339-6, 978-1-4939-3341-9
Authors

Turetschek, Reinhard, Lyon, David, Desalegn, Getinet, Kaul, Hans-Peter, Wienkoop, Stefanie, Reinhard Turetschek, David Lyon, Getinet Desalegn, Hans-Peter Kaul, Stefanie Wienkoop

Editors

Jörg Reinders

Abstract

The proteomic study of non-model organisms, such as many crop plants, is challenging due to the lack of comprehensive genome information. Changing environmental conditions require the study and selection of adapted cultivars. Mutations, inherent to cultivars, hamper protein identification and thus considerably complicate the qualitative and quantitative comparison in large-scale systems biology approaches. With this workflow, cultivar-specific mutations are detected from high-throughput comparative MS analyses, by extracting sequence polymorphisms with de novo sequencing. Stringent criteria are suggested to filter for confidential mutations. Subsequently, these polymorphisms complement the initially used database, which is ready to use with any preferred database search algorithm. In our example, we thereby identified 26 specific mutations in two cultivars of Pisum sativum and achieved an increased number (17 %) of peptide spectrum matches.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Other 4 18%
Researcher 4 18%
Professor > Associate Professor 3 14%
Student > Ph. D. Student 3 14%
Professor 1 5%
Other 2 9%
Unknown 5 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 45%
Biochemistry, Genetics and Molecular Biology 4 18%
Computer Science 1 5%
Social Sciences 1 5%
Medicine and Dentistry 1 5%
Other 1 5%
Unknown 4 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 December 2015.
All research outputs
#18,433,196
of 22,836,570 outputs
Outputs from Methods in molecular biology
#7,921
of 13,126 outputs
Outputs of similar age
#284,429
of 393,568 outputs
Outputs of similar age from Methods in molecular biology
#846
of 1,470 outputs
Altmetric has tracked 22,836,570 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,126 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,470 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.

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