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Proteogenomics

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Attention for Chapter 1: Proteogenomic Tools and Approaches to Explore Protein Coding Landscapes of Eukaryotic Genomes.
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Chapter title
Proteogenomic Tools and Approaches to Explore Protein Coding Landscapes of Eukaryotic Genomes.
Chapter number 1
Book title
Proteogenomics
Published in
Advances in experimental medicine and biology, September 2016
DOI 10.1007/978-3-319-42316-6_1
Pubmed ID
Book ISBNs
978-3-31-942314-2, 978-3-31-942316-6
Authors

Dhirendra Kumar, Debasis Dash

Editors

Ákos Végvári

Abstract

Proteogenomic strategies aim to refine genome-wide annotations of protein coding features by using actual protein level observations. Most of the currently applied proteogenomic approaches include integrative analysis of multiple types of high-throughput omics data, e.g., genomics, transcriptomics, proteomics, etc. Recent efforts towards creating a human proteome map were primarily targeted to experimentally detect at least one protein product for each gene in the genome and extensively utilized proteogenomic approaches. The 14 year long wait to get a draft human proteome map, after completion of similar efforts to sequence the genome, explains the huge complexity and technical hurdles of such efforts. Further, the integrative analysis of large-scale multi-omics datasets inherent to these studies becomes a major bottleneck to their success. However, recent developments of various analysis tools and pipelines dedicated to proteogenomics reduce both the time and complexity of such analysis. Here, we summarize notable approaches, studies, software developments and their potential applications towards eukaryotic genome annotation and clinical proteogenomics.

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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 > Master 6 18%
Student > Ph. D. Student 6 18%
Other 4 12%
Student > Bachelor 3 9%
Student > Doctoral Student 2 6%
Other 4 12%
Unknown 8 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 39%
Agricultural and Biological Sciences 4 12%
Chemistry 2 6%
Nursing and Health Professions 1 3%
Medicine and Dentistry 1 3%
Other 1 3%
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 04 July 2017.
All research outputs
#20,344,065
of 22,890,496 outputs
Outputs from Advances in experimental medicine and biology
#3,973
of 4,952 outputs
Outputs of similar age
#279,615
of 322,482 outputs
Outputs of similar age from Advances in experimental medicine and biology
#97
of 119 outputs
Altmetric has tracked 22,890,496 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 4,952 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 119 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.