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Serum/Plasma Proteomics

Overview of attention for book
Cover of 'Serum/Plasma Proteomics'

Table of Contents

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    Book Overview
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    Chapter 1 Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation
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    Chapter 2 A Protocol for the Preparation of Cryoprecipitate and Cryo-depleted Plasma for Proteomic Studies
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    Chapter 3 Preparation of Platelet Concentrates for Research and Transfusion Purposes
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    Chapter 4 Bead-Based and Multiplexed Immunoassays for Protein Profiling via Sequential Affinity Capture
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    Chapter 5 Affinity Proteomics for Fast, Sensitive, Quantitative Analysis of Proteins in Plasma
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    Chapter 6 Characterization of the Low-Molecular-Weight Human Plasma Peptidome
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    Chapter 7 In-Depth, Reproducible Analysis of Human Plasma Using IgY 14 and SuperMix Immunodepletion
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    Chapter 8 Low-Molecular-Weight Plasma Proteome Analysis Using Top-Down Mass Spectrometry
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    Chapter 9 Identification of Post-Translational Modifications from Serum/Plasma by Immunoaffinity Enrichment and LC-MS/MS Analysis Without Depletion of Abundant Proteins
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    Chapter 10 Identification of Core-Fucosylated Glycoproteome in Human Plasma
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    Chapter 11 Proteomic Analysis of Blood Extracellular Vesicles in Cardiovascular Disease by LC-MS/MS Analysis
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    Chapter 12 Targeted Approach for Proteomic Analysis of a Hidden Membrane Protein
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    Chapter 13 Red Blood Cells in Clinical Proteomics
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    Chapter 14 High-Throughput Quantitative Lipidomics Analysis of Nonesterified Fatty Acids in Plasma by LC-MS
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    Chapter 15 Simultaneous Enrichment of Plasma Extracellular Vesicles and Glycoproteome for Studying Disease Biomarkers
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    Chapter 16 Lipidomics of Human Blood Plasma by High-Resolution Shotgun Mass Spectrometry
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    Chapter 17 Proteomics Analysis of Circulating Serum Exosomes
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    Chapter 18 High-Density Serum/Plasma Reverse Phase Protein Arrays
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    Chapter 19 Antibody Colocalization Microarray for Cross-Reactivity-Free Multiplexed Protein Analysis
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    Chapter 20 Surface Profiling of Extracellular Vesicles from Plasma or Ascites Fluid Using DotScan Antibody Microarrays
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    Chapter 21 Serum Profiling for Identification of Autoantibody Signatures in Diseases Using Protein Microarrays
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    Chapter 22 Quantitative Comparisons of Large Numbers of Human Plasma Samples Using TMT10plex Labeling
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    Chapter 23 Efficient Quantitative Comparisons of Plasma Proteomes Using Label-Free Analysis with MaxQuant
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    Chapter 24 Blood and Plasma Proteomics: Targeted Quantitation and Posttranslational Redox Modifications
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    Chapter 25 SWATH Mass Spectrometry for Proteomics of Non-Depleted Plasma
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    Chapter 26 Shotgun and Targeted Plasma Proteomics to Predict Prognosis of Non-Small Cell Lung Cancer
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    Chapter 27 High-Throughput Parallel Proteomic Sample Preparation Using 96-Well Polyvinylidene Fluoride (PVDF) Membranes and C18 Purification Plates
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    Chapter 28 Targeted Quantification of the Glycated Peptides of Human Serum Albumin
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    Chapter 29 Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics
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    Chapter 30 A Highly Automated Shotgun Proteomic Workflow: Clinical Scale and Robustness for Biomarker Discovery in Blood
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    Chapter 31 Mass Spectrometry-Based Serum Proteomics for Biomarker Discovery and Validation
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    Chapter 32 Metabolomics Toward Biomarker Discovery
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    Chapter 33 Plasma Biomarker Identification and Quantification by Microparticle Proteomics
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    Chapter 34 Bronchoalveolar Lavage: Quantitative Mass Spectrometry-Based Proteomics Analysis in Lung Diseases
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    Chapter 35 Protein Multiplexed Immunoassay Analysis with R
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

13 tweeters


3 Dimensions

Readers on

45 Mendeley
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Serum/Plasma Proteomics
Published by
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-7057-5
978-1-4939-7056-8, 978-1-4939-7057-5

David W. Greening, Richard J. Simpson

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 20%
Student > Ph. D. Student 9 20%
Student > Master 7 16%
Researcher 4 9%
Student > Doctoral Student 2 4%
Other 6 13%
Unknown 8 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 29%
Agricultural and Biological Sciences 8 18%
Medicine and Dentistry 4 9%
Unspecified 2 4%
Chemistry 2 4%
Other 6 13%
Unknown 10 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 27 March 2018.
All research outputs
of 12,713,955 outputs
Outputs from Methods in molecular biology
of 8,369 outputs
Outputs of similar age
of 261,743 outputs
Outputs of similar age from Methods in molecular biology
of 5 outputs
Altmetric has tracked 12,713,955 research outputs across all sources so far. Compared to these this one has done well and is in the 77th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,369 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 261,743 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.