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A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks

Overview of attention for article published in PLOS ONE, February 2010
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Title
A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks
Published in
PLOS ONE, February 2010
DOI 10.1371/journal.pone.0009289
Pubmed ID
Authors

Etsuko Miyamoto-Sato, Shigeo Fujimori, Masamichi Ishizaka, Naoya Hirai, Kazuyo Masuoka, Rintaro Saito, Yosuke Ozawa, Katsuya Hino, Takanori Washio, Masaru Tomita, Tatsuhiro Yamashita, Tomohiro Oshikubo, Hidetoshi Akasaka, Jun Sugiyama, Yasuo Matsumoto, Hiroshi Yanagawa

Abstract

Large-scale data sets of protein-protein interactions (PPIs) are a valuable resource for mapping and analysis of the topological and dynamic features of interactome networks. The currently available large-scale PPI data sets only contain information on interaction partners. The data presented in this study also include the sequences involved in the interactions (i.e., the interacting regions, IRs) suggested to correspond to functional and structural domains. Here we present the first large-scale IR data set obtained using mRNA display for 50 human transcription factors (TFs), including 12 transcription-related proteins. The core data set (966 IRs; 943 PPIs) displays a verification rate of 70%. Analysis of the IR data set revealed the existence of IRs that interact with multiple partners. Furthermore, these IRs were preferentially associated with intrinsic disorder. This finding supports the hypothesis that intrinsically disordered regions play a major role in the dynamics and diversity of TF networks through their ability to structurally adapt to and bind with multiple partners. Accordingly, this domain-based interaction resource represents an important step in refining protein interactions and networks at the domain level and in associating network analysis with biological structure and function.

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Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 2 2%
Germany 1 1%
France 1 1%
Hungary 1 1%
United Kingdom 1 1%
Hong Kong 1 1%
Mexico 1 1%
Poland 1 1%
Unknown 73 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 34%
Student > Ph. D. Student 18 22%
Student > Master 6 7%
Professor > Associate Professor 5 6%
Student > Postgraduate 4 5%
Other 11 13%
Unknown 10 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 54%
Biochemistry, Genetics and Molecular Biology 14 17%
Medicine and Dentistry 4 5%
Neuroscience 3 4%
Computer Science 2 2%
Other 5 6%
Unknown 10 12%