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Regular Patterns for Proteome-Wide Distribution of Protein Abundance across Species

Overview of attention for article published in PLOS ONE, March 2012
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Title
Regular Patterns for Proteome-Wide Distribution of Protein Abundance across Species
Published in
PLOS ONE, March 2012
DOI 10.1371/journal.pone.0032423
Pubmed ID
Authors

Fan Zhong, Dong Yang, Yunwei Hao, Chengzhao Lin, Ying Jiang, Wantao Ying, Songfeng Wu, Yunping Zhu, Siqi Liu, Pengyuan Yang, Xiaohong Qian, Fuchu He

Abstract

A proteome of the bio-entity, including cell, tissue, organ, and organism, consists of proteins of diverse abundance. The principle that determines the abundance of different proteins in a proteome is of fundamental significance for an understanding of the building blocks of the bio-entity. Here, we report three regular patterns in the proteome-wide distribution of protein abundance across species such as human, mouse, fly, worm, yeast, and bacteria: in most cases, protein abundance is positively correlated with the protein's origination time or sequence conservation during evolution; it is negatively correlated with the protein's domain number and positively correlated with domain coverage in protein structure, and the correlations became stronger during the course of evolution; protein abundance can be further stratified by the function of the protein, whereby proteins that act on material conversion and transportation (mass category) are more abundant than those that act on information modulation (information category). Thus, protein abundance is intrinsically related to the protein's inherent characters of evolution, structure, and function.

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The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Japan 1 3%
Netherlands 1 3%
Brazil 1 3%
Unknown 28 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 31%
Student > Ph. D. Student 7 22%
Other 3 9%
Student > Bachelor 2 6%
Professor 2 6%
Other 4 13%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 38%
Biochemistry, Genetics and Molecular Biology 6 19%
Environmental Science 3 9%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Veterinary Science and Veterinary Medicine 1 3%
Other 4 13%
Unknown 5 16%