Notice of Retraction: Dynamic Nucleosome Positioning around Functional Transcription Factor Binding Sites in the Promoters of Inducible NF-kappaB Target Genes

Author(s):  
Yumin Nie ◽  
Xiao Sun
2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
J. Sunil Rao ◽  
Suresh Karanam ◽  
Colleen D. McCabe ◽  
Carlos S. Moreno

Background. The computational identification of functional transcription factor binding sites (TFBSs) remains a major challenge of computational biology. Results. We have analyzed the conserved promoter sequences for the complete set of human RefSeq genes using our conserved transcription factor binding site (CONFAC) software. CONFAC identified 16296 human-mouse ortholog gene pairs, and of those pairs, 9107 genes contained conserved TFBS in the 3 kb proximal promoter and first intron. To attempt to predict in vivo occupancy of transcription factor binding sites, we developed a novel marginal effect isolator algorithm that builds upon Bayesian methods for multigroup TFBS filtering and predicted the in vivo occupancy of two transcription factors with an overall accuracy of 84%. Conclusion. Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo.


2015 ◽  
Vol 44 (8) ◽  
pp. e72-e72 ◽  
Author(s):  
Stefan H. Lelieveld ◽  
Judith Schütte ◽  
Maurits J.J. Dijkstra ◽  
Punto Bawono ◽  
Sarah J. Kinston ◽  
...  

2005 ◽  
Vol preprint (2006) ◽  
pp. e130
Author(s):  
Alan M. Moses ◽  
Daniel Pollard ◽  
David A Nix ◽  
Venky N. Iyer ◽  
Xiao-Yong Li ◽  
...  

2020 ◽  
Vol 26 (42) ◽  
pp. 7641-7654 ◽  
Author(s):  
Tao Ma ◽  
Zhenqing Ye ◽  
Liguo Wang

Background: Transcription factors are DNA-binding proteins that play key roles in many fundamental biological processes. Unraveling their interactions with DNA is essential to identify their target genes and understand the regulatory network. Genome-wide identification of their binding sites became feasible thanks to recent progress in experimental and computational approaches. ChIP-chip, ChIP-seq, and ChIP-exo are three widely used techniques to demarcate genome-wide transcription factor binding sites. Objective: This review aims to provide an overview of these three techniques including their experiment procedures, computational approaches, and popular analytic tools. Conclusion: ChIP-chip, ChIP-seq, and ChIP-exo have been the major techniques to study genome- wide in vivo protein-DNA interaction. Due to the rapid development of next-generation sequencing technology, array-based ChIP-chip is deprecated and ChIP-seq has become the most widely used technique to identify transcription factor binding sites in genome-wide. The newly developed ChIP-exo further improves the spatial resolution to single nucleotide. Numerous tools have been developed to analyze ChIP-chip, ChIP-seq and ChIP-exo data. However, different programs may employ different mechanisms or underlying algorithms thus each will inherently include its own set of statistical assumption and bias. So choosing the most appropriate analytic program for a given experiment needs careful considerations. Moreover, most programs only have command line interface so their installation and usage will require basic computation expertise in Unix/Linux.


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