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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.
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    Chapter 3 Choosing an Optimal Database for Protein Identification from Tandem Mass Spectrometry Data.
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    Chapter 4 Label-Based and Label-Free Strategies for Protein Quantitation.
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    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?
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    Chapter 7 Methods to Calculate Spectrum Similarity.
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    Chapter 8 Proteotypic Peptides and Their Applications.
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    Chapter 9 Statistical Evaluation of Labeled Comparative Profiling Proteomics Experiments Using Permutation Test.
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    Chapter 10 De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data.
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    Chapter 11 Phylogenetic Analysis Using Protein Mass Spectrometry.
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    Chapter 12 Bioinformatics Methods to Deduce Biological Interpretation from Proteomics Data.
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    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.
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    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 1: An Introduction to Proteome Bioinformatics.
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Chapter title
An Introduction to Proteome Bioinformatics.
Chapter number 1
Book title
Proteome Bioinformatics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6740-7_1
Pubmed ID
27975279
Book ISBNs
978-1-4939-6738-4, 978-1-4939-6740-7
Authors

Shivakumar Keerthikumar, Keerthikumar, Shivakumar

Editors

Shivakumar Keerthikumar, Suresh Mathivanan

Abstract

High-throughput techniques are indispensable for aiding basic and translational research. Among them, recent advances in proteomics techniques have allowed biomedical researchers to characterize the proteome of multiple organisms. This remarkable advancement have been well complemented by proteome bioinformatics methods and tools. Proteome bioinformatics refers to the study and application of informatics in the field of proteomics. This chapter provides an overview of computational strategies, methods, and techniques reported in this book for bioinformatics analysis of protein data. An outline of many bioinformatics tools, databases, and proteomic techniques described in each of the chapters is given here.

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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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 15%
Student > Doctoral Student 4 12%
Researcher 4 12%
Student > Ph. D. Student 3 9%
Student > Master 2 6%
Other 4 12%
Unknown 11 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 18%
Medicine and Dentistry 4 12%
Agricultural and Biological Sciences 3 9%
Computer Science 3 9%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Other 4 12%
Unknown 11 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 19 December 2016.
All research outputs
#20,365,559
of 22,914,829 outputs
Outputs from Methods in molecular biology
#9,921
of 13,131 outputs
Outputs of similar age
#355,358
of 420,479 outputs
Outputs of similar age from Methods in molecular biology
#842
of 1,074 outputs
Altmetric has tracked 22,914,829 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,131 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 420,479 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,074 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.

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