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Modern Proteomics – Sample Preparation, Analysis and Practical Applications

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Cover of 'Modern Proteomics – Sample Preparation, Analysis and Practical Applications'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Proteomes, Their Compositions and Their Sources
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    Chapter 2 Protein Fractionation and Enrichment Prior to Proteomics Sample Preparation
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    Chapter 3 Sample Preparation for Mass Spectrometry-Based Proteomics; from Proteomes to Peptides
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    Chapter 4 Plant Structure and Specificity – Challenges and Sample Preparation Considerations for Proteomics
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    Chapter 5 Improving Proteome Coverage by Reducing Sample Complexity via Chromatography
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    Chapter 6 Database Search Engines: Paradigms, Challenges and Solutions
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    Chapter 7 Mass Analyzers and Mass Spectrometers
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    Chapter 8 Top-Down Mass Spectrometry: Proteomics to Proteoforms
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    Chapter 9 Platforms and Pipelines for Proteomics Data Analysis and Management
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    Chapter 10 Tandem Mass Spectrum Sequencing: An Alternative to Database Search Engines in Shotgun Proteomics
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    Chapter 11 Visualization, Inspection and Interpretation of Shotgun Proteomics Identification Results
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    Chapter 12 Protein Inference
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    Chapter 13 Modification Site Localization in Peptides
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    Chapter 14 Useful Web Resources
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    Chapter 15 Mass Spectrometry-Based Protein Quantification
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    Chapter 16 Bioinformatics Tools for Proteomics Data Interpretation
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    Chapter 17 Identification, Quantification, and Site Localization of Protein Posttranslational Modifications via Mass Spectrometry-Based Proteomics
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    Chapter 18 Protein-Protein Interaction Detection Via Mass Spectrometry-Based Proteomics
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    Chapter 19 Protein Structural Analysis via Mass Spectrometry-Based Proteomics
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    Chapter 20 Introduction to Clinical Proteomics
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    Chapter 21 Discovery of Candidate Biomarkers
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    Chapter 22 Statistical Approaches to Candidate Biomarker Panel Selection
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    Chapter 23 Qualification and Verification of Protein Biomarker Candidates
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    Chapter 24 Protocol for Standardizing High-to-Moderate Abundance Protein Biomarker Assessments Through an MRM-with-Standard-Peptides Quantitative Approach
Attention for Chapter 16: Bioinformatics Tools for Proteomics Data Interpretation
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Chapter title
Bioinformatics Tools for Proteomics Data Interpretation
Chapter number 16
Book title
Modern Proteomics – Sample Preparation, Analysis and Practical Applications
Published in
Advances in experimental medicine and biology, December 2016
DOI 10.1007/978-3-319-41448-5_16
Pubmed ID
Book ISBNs
978-3-31-941446-1, 978-3-31-941448-5
Authors

Karla Grisel Calderón-González, Jesús Hernández-Monge, María Esther Herrera-Aguirre, Juan Pedro Luna-Arias

Editors

Hamid Mirzaei, Martin Carrasco

Abstract

Biological systems function via intricate cellular processes and networks in which RNAs, metabolites, proteins and other cellular compounds have a precise role and are exquisitely regulated (Kumar and Mann, FEBS Lett 583(11):1703-1712, 2009). The development of high-throughput technologies, such as the Next Generation DNA Sequencing (NGS) and DNA microarrays for sequencing genomes or metagenomes, have triggered a dramatic increase in the last few years in the amount of information stored in the GenBank and UniProt Knowledgebase (UniProtKB). GenBank release 210, reported in October 2015, contains 202,237,081,559 nucleotides corresponding to 188,372,017 sequences, whilst there are only 1,222,635,267,498 nucleotides corresponding to 309,198,943 sequences from Whole Genome Shotgun (WGS) projects. In the case of UniProKB/Swiss-Prot, release 2015_12 (December 9, 2015) contains 196,219,159 amino acids that correspond to 550,116 entries. Meanwhile, UniProtKB/TrEMBL (release 2015_12 of December 9 2015) contains 1,838,851,8871 amino acids corresponding to 555,270,679 entries. Proteomics has also improved our knowledge of proteins that are being expressed in cells at a certain time of the cell cycle. It has also allowed the identification of molecules forming part of multiprotein complexes and an increasing number of posttranslational modifications (PTMs) that are present in proteins, as well as the variants of proteins expressed.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 2%
Unknown 50 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 20%
Student > Bachelor 6 12%
Researcher 5 10%
Student > Master 3 6%
Student > Doctoral Student 2 4%
Other 8 16%
Unknown 17 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 29%
Agricultural and Biological Sciences 8 16%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Engineering 2 4%
Chemistry 2 4%
Other 5 10%
Unknown 17 33%
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 02 October 2017.
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#18,171,423
of 23,344,526 outputs
Outputs from Advances in experimental medicine and biology
#3,154
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Outputs of similar age
#295,566
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Outputs of similar age from Advances in experimental medicine and biology
#322
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So far Altmetric has tracked 4,997 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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