↓ Skip to main content

Global Mapping of Transcription Factor Binding Sites by Sequencing Chromatin Surrogates: a Perspective on Experimental Design, Data Analysis, and Open Problems

Overview of attention for article published in Statistics in Biosciences, May 2012
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
24 Mendeley
Title
Global Mapping of Transcription Factor Binding Sites by Sequencing Chromatin Surrogates: a Perspective on Experimental Design, Data Analysis, and Open Problems
Published in
Statistics in Biosciences, May 2012
DOI 10.1007/s12561-012-9066-5
Pubmed ID
Authors

Yingying Wei, George Wu, Hongkai Ji

Abstract

Mapping genome-wide binding sites of all transcription factors (TFs) in all biological contexts is a critical step toward understanding gene regulation. The state-of-the-art technologies for mapping transcription factor binding sites (TFBSs) couple chromatin immunoprecipitation (ChIP) with high-throughput sequencing (ChIP-seq) or tiling array hybridization (ChIP-chip). These technologies have limitations: they are low-throughput with respect to surveying many TFs. Recent advances in genome-wide chromatin profiling, including development of technologies such as DNase-seq, FAIRE-seq and ChIP-seq for histone modifications, make it possible to predict in vivo TFBSs by analyzing chromatin features at computationally determined DNA motif sites. This promising new approach may allow researchers to monitor the genome-wide binding sites of many TFs simultaneously. In this article, we discuss various experimental design and data analysis issues that arise when applying this approach. Through a systematic analysis of the data from the Encyclopedia Of DNA Elements (ENCODE) project, we compare the predictive power of individual and combinations of chromatin marks using supervised and unsupervised learning methods, and evaluate the value of integrating information from public ChIP and gene expression data. We also highlight the challenges and opportunities for developing novel analytical methods, such as resolving the one-motif-multiple-TF ambiguity and distinguishing functional and non-functional TF binding targets from the predicted binding sites.

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

Geographical breakdown

Country Count As %
Mexico 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 25%
Student > Ph. D. Student 4 17%
Student > Master 3 13%
Professor > Associate Professor 2 8%
Professor 1 4%
Other 3 13%
Unknown 5 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 25%
Agricultural and Biological Sciences 5 21%
Medicine and Dentistry 3 13%
Mathematics 1 4%
Economics, Econometrics and Finance 1 4%
Other 3 13%
Unknown 5 21%
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 06 May 2013.
All research outputs
#17,285,036
of 25,373,627 outputs
Outputs from Statistics in Biosciences
#42
of 76 outputs
Outputs of similar age
#116,603
of 177,809 outputs
Outputs of similar age from Statistics in Biosciences
#5
of 7 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 76 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 34th percentile – i.e., 34% 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 177,809 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% 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 2 of them.