↓ Skip to main content

The Biochemistry of Retinoic Acid Receptors I: Structure, Activation, and Function at the Molecular Level

Overview of attention for book
Attention for Chapter 10: Complexity of the RAR-Mediated Transcriptional Regulatory Programs.
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
14 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Complexity of the RAR-Mediated Transcriptional Regulatory Programs.
Chapter number 10
Book title
The Biochemistry of Retinoic Acid Receptors I: Structure, Activation, and Function at the Molecular Level
Published in
Sub cellular biochemistry, June 2014
DOI 10.1007/978-94-017-9050-5_10
Pubmed ID
Book ISBNs
978-9-40-179049-9, 978-9-40-179050-5
Authors

Zhijie Liu, Qidong Hu, Michael G Rosenfeld, Michael G. Rosenfeld

Editors

Mary Ann Asson-Batres, Cécile Rochette-Egly

Abstract

In the past several decades, intensive research in this field has uncovered a surprising number of regulatory factors and their associated enzymatic properties to reveal the network of complexes that function in activation and repression of the transcriptional programs mediated by nuclear receptors (NR). These factors and their associated complexes have been extensively characterized both biochemically and functionally [34, 87, 94]. Several principles have emerged: (1) It is widely recognized that ligand-dependent cofactor complexes mediating repression and activation exhibit ligand-dependent exchange. (2) These complexes mediate modifications of chromatin structure consequent to their binding at regulatory elements, particularly at promoter and enhancer Enhancer sites. (3) The concept about the rapid exchange of coregulatory complexes at regulatory sites has been suggested [88]. Key questions in the NR field have included: (a) What are the cofactors and exchange complexes used to mediate the ligand and signaling network-dependent switches in gene regulation programs; (b) Do long non-coding RNAs (lncRNAs) serve as regulatory "factors" for ligand-dependent gene programs, and do enhancers actually regulate transcription units encoding enhancer Enhancer non-coding RNAs (eRNAs) Enhancer RNA that might have functional significance; (c) What is the relationship between DNA damage repair machinery and transcriptional machinery? (d) Do Retinoic Acid Receptors (RAR) also regulate Pol III-dependent, non-coding repeat transcriptional units in stem cells? and (e) How have new technologies such as deep sequencing altered our ability to investigate transcriptional regulatory mechanisms utilized by NRs?

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

Geographical breakdown

Country Count As %
Poland 1 7%
Unknown 13 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 36%
Student > Ph. D. Student 2 14%
Lecturer 1 7%
Student > Bachelor 1 7%
Student > Master 1 7%
Other 1 7%
Unknown 3 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 21%
Agricultural and Biological Sciences 3 21%
Computer Science 1 7%
Medicine and Dentistry 1 7%
Neuroscience 1 7%
Other 0 0%
Unknown 5 36%
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 26 June 2014.
All research outputs
#18,373,874
of 22,757,541 outputs
Outputs from Sub cellular biochemistry
#237
of 354 outputs
Outputs of similar age
#163,780
of 227,908 outputs
Outputs of similar age from Sub cellular biochemistry
#3
of 7 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 354 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 16th percentile – i.e., 16% 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 227,908 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.