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Transcription Factor Regulatory Networks

Overview of attention for book
Cover of 'Transcription Factor Regulatory Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Detecting protein-protein interactions/complex components using mass spectrometry coupled techniques.
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    Chapter 2 Analysis of Transcription Factor Networks Using IVV Method
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    Chapter 3 Next-generation sequencing coupled with a cell-free display technology for reliable interactome of translational factors.
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    Chapter 4 Chromatin immunoprecipitation protocol for Mammalian cells.
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    Chapter 5 Detecting Protein-DNA Interactions Using a Modified Yeast One-Hybrid System.
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    Chapter 6 RNA Sequencing: From Sample Preparation to Analysis
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    Chapter 7 Detecting Expressed Genes Using CAGE.
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    Chapter 8 A tutorial to identify nonlinear associations in gene expression time series data.
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    Chapter 9 Inference of TFRNs (2)
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    Chapter 10 Identification of the minimal connected network of transcription factors by transcriptomic and genomic data integration.
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    Chapter 11 Modeling and Simulation Using CellDesigner
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    Chapter 12 Human Genome Network Platform: A Resource for TFRN Analysis.
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    Chapter 13 Identification of Transcription Factors Activated in Thymic Epithelial Cells During Embryonic Thymus Development
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    Chapter 14 Analysis of NFATc1-Centered Transcription Factor Regulatory Networks in Osteoclast Formation
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    Chapter 15 Transcriptional Regulation in Adipogenesis Through PPARγ-Dependent and -Independent Mechanisms by Prostaglandins.
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    Chapter 16 Analysis of TFRNs Associated with Steroid Hormone-Related Cancers.
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    Chapter 17 Repositioning Monocyte TFRN into Fibroblasts
Overall attention for this book and its chapters
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Mentioned by

1 blog
17 tweeters
2 Facebook pages
1 Wikipedia page
1 Google+ user


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98 Mendeley
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Transcription Factor Regulatory Networks
Published by
Springer New York, June 2014
DOI 10.1007/978-1-4939-0805-9
978-1-4939-0804-2, 978-1-4939-0805-9

Miyamoto-Sato, Etsuko, Ohashi, Hiroyuki, Sasaki, Hirotaka, Nishikawa, Jun-ichi, Yanagawa, Hiroshi

Twitter Demographics

The data shown below were collected from the profiles of 17 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Denmark 1 1%
Brazil 1 1%
Japan 1 1%
Indonesia 1 1%
Unknown 91 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 35%
Researcher 15 15%
Student > Doctoral Student 10 10%
Student > Bachelor 7 7%
Student > Master 7 7%
Other 17 17%
Unknown 8 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 44%
Biochemistry, Genetics and Molecular Biology 25 26%
Medicine and Dentistry 6 6%
Engineering 5 5%
Immunology and Microbiology 2 2%
Other 5 5%
Unknown 12 12%