Identifying Combinatorial Transcription Factor Interactions with Microarray Data and ChIP-Chip Data

2008 ◽  
Author(s):  
Ting Chen ◽  
Feng Li
Keyword(s):  
Transcription Factor ◽  
Microarray Data ◽  
Chip Data ◽  
Factor Interactions ◽  
Chip Chip

scholarly journals Mining ChIP-chip data for transcription factor and cofactor binding sites

2005 ◽  
Vol 21 (Suppl 1) ◽  
pp. i403-i412 ◽  
Author(s):  
A. D. Smith ◽  
P. Sumazin ◽  
D. Das ◽  
M. Q. Zhang
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Chip Data ◽  
Cofactor Binding ◽  
Chip Chip

Proteomic analysis of transcription factor interactions in myeloid stem cell development and leukaemia

2002 ◽  
Vol 6 (4) ◽  
pp. 491-495 ◽  
Author(s):  
Gerhard Behre ◽  
Venkateshwar A Reddy ◽  
Daniel G Tenen ◽  
Wolfgang Hiddemann ◽  
Abdul A Peer Zada ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Stem Cell ◽  
Proteomic Analysis ◽  
Cell Development ◽  
Factor Interactions

scholarly journals Discovering human transcription factor interactions with genetic variants, novel DNA motifs, and repetitive elements using enhanced yeast one-hybrid assays

2018 ◽  
Author(s):  
Shaleen Shrestha ◽  
Jared Allan Sewell ◽  
Clarissa Stephanie Santoso ◽  
Elena Forchielli ◽  
Sebastian Carrasco Pro ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Hormone Receptors ◽  
Single Nucleotide Variants ◽  
Alu Elements ◽  
Dna Motifs ◽  
Super Enhancer ◽  
Dna Elements ◽  
Genomic Regions ◽  
Factor Interactions ◽  
Ets Factors

ABSTRACTIdentifying transcription factor (TF) binding to noncoding variants, uncharacterized DNA motifs, and repetitive genomic elements has been technically and computationally challenging. Current experimental methods, such as chromatin immunoprecipitation, generally test one TF at a time, and computational motif algorithms often lead to false positive and negative predictions. To address these limitations, we developed two approaches based on enhanced yeast one-hybrid assays. The first approach interrogates the binding of >1,000 human TFs to repetitive DNA elements, while the second evaluates TF binding to single nucleotide variants, short insertions and deletions (indels), and novel DNA motifs. Using the first approach, we detected the binding of 75 TFs, including several nuclear hormone receptors and ETS factors, to the highly repetitive Alu elements. Using the second approach, we identified cancer-associated changes in TF binding, including gain of interactions involving ETS TFs and loss of interactions involving KLF TFs to different mutations in the TERT promoter, and gain of a MYB interaction with an 18 bp indel in the TAL1 super-enhancer. Additionally, we identified the TFs that bind to three uncharacterized DNA motifs identified in DNase footprinting assays. We anticipate that these approaches will expand our capabilities to study genetic variation and under-characterized genomic regions.

Inferring transcription factor activity from microarray data reveals novel targets for toxicological investigations

Toxicology ◽  
2017 ◽  
Vol 389 ◽  
pp. 101-107 ◽  
Author(s):  
T.M. Souza ◽  
T. van den Beucken ◽  
J.C.S. Kleinjans ◽  
D.G.J. Jennen
Keyword(s):  
Transcription Factor ◽  
Microarray Data ◽  
Transcription Factor Activity ◽  
Factor Activity ◽  
Novel Targets

scholarly journals A highly efficient and effective motif discovery method for ChIP-seq/ChIP-chip data using positional information

2011 ◽  
Vol 40 (7) ◽  
pp. e50-e50 ◽  
Author(s):  
Xiaotu Ma ◽  
Ashwinikumar Kulkarni ◽  
Zhihua Zhang ◽  
Zhenyu Xuan ◽  
Robert Serfling ◽  
...  
Keyword(s):  
Motif Discovery ◽  
Positional Information ◽  
Chip Data ◽  
Highly Efficient ◽  
Discovery Method ◽  
Chip Chip

scholarly journals De novo identification of in vivo binding sites from ChIP-chip data

2008 ◽  
Vol 9 (S7) ◽  
Author(s):  
Victor Jin ◽  
Alina Rabinovich ◽  
Henny O'Geen ◽  
Sushma Iyengar ◽  
Peggy Farnham
Keyword(s):  
Binding Sites ◽  
De Novo ◽  
Chip Data ◽  
In Vivo Binding ◽  
Chip Chip
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