↓ Skip to main content
What is this page? Embed badge

Proteome Bioinformatics

Overview of attention for book
Cover of 'Proteome Bioinformatics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 An Introduction to Proteome Bioinformatics.
  3. Altmetric Badge
    Chapter 2 Proteomic Data Storage and Sharing.
  4. Altmetric Badge
    Chapter 3 Choosing an Optimal Database for Protein Identification from Tandem Mass Spectrometry Data.
  5. Altmetric Badge
    Chapter 4 Label-Based and Label-Free Strategies for Protein Quantitation.
  6. Altmetric Badge
    Chapter 5 TMT One-Stop Shop: From Reliable Sample Preparation to Computational Analysis Platform.
  7. Altmetric Badge
    Chapter 6 Unassigned MS/MS Spectra: Who Am I?
  8. Altmetric Badge
    Chapter 7 Methods to Calculate Spectrum Similarity.
  9. Altmetric Badge
    Chapter 8 Proteotypic Peptides and Their Applications.
  10. Altmetric Badge
    Chapter 9 Statistical Evaluation of Labeled Comparative Profiling Proteomics Experiments Using Permutation Test.
  11. Altmetric Badge
    Chapter 10 De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data.
  12. Altmetric Badge
    Chapter 11 Phylogenetic Analysis Using Protein Mass Spectrometry.
  13. Altmetric Badge
    Chapter 12 Bioinformatics Methods to Deduce Biological Interpretation from Proteomics Data.
  14. Altmetric Badge
    Chapter 13 A Systematic Bioinformatics Approach to Identify High Quality Mass Spectrometry Data and Functionally Annotate Proteins and Proteomes.
  15. Altmetric Badge
    Chapter 14 Network Tools for the Analysis of Proteomic Data.
  16. Altmetric Badge
    Chapter 15 Determining the Significance of Protein Network Features and Attributes Using Permutation Testing.
  17. Altmetric Badge
    Chapter 16 Bioinformatics Tools and Resources for Analyzing Protein Structures.
  18. Altmetric Badge
    Chapter 17 In Silico Approach to Identify Potential Inhibitors for Axl-Gas6 Signaling.
Attention for Chapter 4: Label-Based and Label-Free Strategies for Protein Quantitation.
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
1 blog
twitter
1 X user

Readers on

mendeley
110 Mendeley
Summary Blogs X
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Label-Based and Label-Free Strategies for Protein Quantitation.
Chapter number 4
Book title
Proteome Bioinformatics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6740-7_4
Pubmed ID
27975282
Book ISBNs
978-1-4939-6738-4, 978-1-4939-6740-7
Authors

Sushma Anand, Monisha Samuel, Ching-Seng Ang, Shivakumar Keerthikumar, Suresh Mathivanan, Anand, Sushma, Samuel, Monisha, Ang, Ching-Seng, Keerthikumar, Shivakumar, Mathivanan, Suresh

Editors

Shivakumar Keerthikumar, Suresh Mathivanan

Abstract

The precise quantification of changes between various physiological states in a biological system is highly complex in nature. Over the past few years, in combination with classical methods, mass spectrometry based approaches have become an indispensable tool in deciphering exact abundance of proteins in composite mixtures. The technique is now well established and employs both label-based and label-free quantitation strategies. Label-based quantitation methods utilize stable isotope labels which are incorporated within the peptides, introducing an expectable mass difference within the two or more experimental conditions. In contrast, label-free proteomics quantitates both relative and absolute protein quantity by utilizing signal intensity and spectral counting of peptides. This chapter focuses on the commonly used quantitative mass spectrometry methods for high-throughput proteomic analysis.

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 110 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 18 16%
Student > Ph. D. Student 15 14%
Researcher 12 11%
Student > Master 12 11%
Student > Postgraduate 7 6%
Other 14 13%
Unknown 32 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 33 30%
Agricultural and Biological Sciences 9 8%
Chemistry 8 7%
Pharmacology, Toxicology and Pharmaceutical Science 5 5%
Medicine and Dentistry 5 5%
Other 15 14%
Unknown 35 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 08 December 2022.
All research outputs
#4,182,788
of 23,292,144 outputs
Outputs from Methods in molecular biology
#1,090
of 13,334 outputs
Outputs of similar age
#82,617
of 422,721 outputs
Outputs of similar age from Methods in molecular biology
#125
of 1,076 outputs
Altmetric has tracked 23,292,144 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,334 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 91% 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 422,721 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 1,076 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.

This page is provided by Altmetric.