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Mass Spectrometry Data Analysis in Proteomics

Overview of attention for book
Cover of 'Mass Spectrometry Data Analysis in Proteomics'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Mass Spectrometry-Based Proteomics
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    Chapter 2 LC-MS Spectra Processing
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    Chapter 3 Isotopic Distributions
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    Chapter 4 Retention Time Prediction and Protein Identification
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    Chapter 5 Comparing Peptide Spectra Matches Across Search Engines
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    Chapter 6 Calculation of False Discovery Rate for Peptide and Protein Identification
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    Chapter 7 Methods and Algorithms for Quantitative Proteomics by Mass Spectrometry
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    Chapter 8 Interpretation of Tandem Mass Spectra of Posttranslationally Modified Peptides
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    Chapter 9 Solution to Dark Matter Identified by Mass-Tolerant Database Search
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    Chapter 10 Phosphoproteomics Profiling to Identify Altered Signaling Pathways and Kinase-Targeted Cancer Therapies
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    Chapter 11 Mass Spectrometry-Based Characterization of Ub- and UbL-Modified Proteins
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    Chapter 12 Targeted Proteomics as a Tool for Quantifying Urine-Based Biomarkers
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    Chapter 13 Data Imputation in Merged Isobaric Labeling-Based Relative Quantification Datasets
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    Chapter 14 Clustering Clinical Data in R
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    Chapter 15 Review of Issues and Solutions to Data Analysis Reproducibility and Data Quality in Clinical Proteomics
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    Chapter 16 Review of Batch Effects Prevention, Diagnostics, and Correction Approaches
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    Chapter 17 Using the Object-Oriented PowerShell for Simple Proteomics Data Analysis
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    Chapter 18 Considerations in the Analysis of Hydrogen Exchange Mass Spectrometry Data
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
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

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3 Wikipedia pages

Citations

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Title
Mass Spectrometry Data Analysis in Proteomics
Published by
Methods in molecular biology, January 2020
DOI 10.1007/978-1-4939-9744-2
ISBNs
978-1-4939-9743-5, 978-1-4939-9744-2
Editors

Rune Matthiesen

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X Demographics

The data shown below were collected from the profiles of 24 X users who shared this research output. Click here to find out more about how the information was compiled.
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 November 2023.
All research outputs
#2,328,689
of 25,663,438 outputs
Outputs from Methods in molecular biology
#351
of 14,322 outputs
Outputs of similar age
#55,502
of 479,108 outputs
Outputs of similar age from Methods in molecular biology
#8
of 121 outputs
Altmetric has tracked 25,663,438 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,322 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 97% 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 479,108 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 88% of its contemporaries.
We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.