Literature DB >> 17825010

ChIP-chip: data, model, and analysis.

Ming Zheng1, Leah O Barrera, Bing Ren, Ying Nian Wu.   

Abstract

ChIP-chip (or ChIP-on-chip) is a technology for isolation and identification of genomic sites occupied by specific DNA-binding proteins in living cells. The ChIP-chip signals can be obtained over the whole genome by tiling arrays, where a peak shape is generally observed around a protein-binding site. In this article, we describe the ChIP-chip process and present a probability model for ChIP-chip data. We then propose a model-based method for recognizing the peak shapes for the purpose of detecting protein-binding sites. We also investigate the issue of bandwidth in nonparametric kernel smoothing method.

Mesh:

Substances:

Year:  2007        PMID: 17825010     DOI: 10.1111/j.1541-0420.2007.00768.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  36 in total

Review 1.  DNA-protein interactions: methods for detection and analysis.

Authors:  Bipasha Dey; Sameer Thukral; Shruti Krishnan; Mainak Chakrobarty; Sahil Gupta; Chanchal Manghani; Vibha Rani
Journal:  Mol Cell Biochem       Date:  2012-03-08       Impact factor: 3.396

2.  JAMIE: joint analysis of multiple ChIP-chip experiments.

Authors:  Hao Wu; Hongkai Ji
Journal:  Bioinformatics       Date:  2010-06-15       Impact factor: 6.937

3.  ChIP-on-chip significance analysis reveals large-scale binding and regulation by human transcription factor oncogenes.

Authors:  Adam A Margolin; Teresa Palomero; Pavel Sumazin; Andrea Califano; Adolfo A Ferrando; Gustavo Stolovitzky
Journal:  Proc Natl Acad Sci U S A       Date:  2008-12-31       Impact factor: 11.205

4.  Transcriptional enhancement by GATA1-occupied DNA segments is strongly associated with evolutionary constraint on the binding site motif.

Authors:  Yong Cheng; David C King; Louis C Dore; Xinmin Zhang; Yuepin Zhou; Ying Zhang; Christine Dorman; Demesew Abebe; Swathi A Kumar; Francesca Chiaromonte; Webb Miller; Roland D Green; Mitchell J Weiss; Ross C Hardison
Journal:  Genome Res       Date:  2008-09-25       Impact factor: 9.043

5.  Epigenetic change detection and pattern recognition via Bayesian hierarchical hidden Markov models.

Authors:  Xinlei Wang; Miao Zang; Guanghua Xiao
Journal:  Stat Med       Date:  2012-10-25       Impact factor: 2.373

6.  Genome-scale reconstruction of the Lrp regulatory network in Escherichia coli.

Authors:  Byung-Kwan Cho; Christian L Barrett; Eric M Knight; Young Seoub Park; Bernhard Ø Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2008-12-03       Impact factor: 11.205

7.  CoCAS: a ChIP-on-chip analysis suite.

Authors:  Touati Benoukraf; Pierre Cauchy; Romain Fenouil; Adrien Jeanniard; Frederic Koch; Sébastien Jaeger; Denis Thieffry; Jean Imbert; Jean-Christophe Andrau; Salvatore Spicuglia; Pierre Ferrier
Journal:  Bioinformatics       Date:  2009-02-04       Impact factor: 6.937

8.  Primary sequence and epigenetic determinants of in vivo occupancy of genomic DNA by GATA1.

Authors:  Ying Zhang; Weisheng Wu; Yong Cheng; David C King; Robert S Harris; James Taylor; Francesca Chiaromonte; Ross C Hardison
Journal:  Nucleic Acids Res       Date:  2009-11       Impact factor: 16.971

9.  Improved ChIP-chip analysis by a mixture model approach.

Authors:  Wei Sun; Michael J Buck; Mukund Patel; Ian J Davis
Journal:  BMC Bioinformatics       Date:  2009-06-07       Impact factor: 3.169

10.  Bayesian modeling of ChIP-chip data using latent variables.

Authors:  Mingqi Wu; Faming Liang; Yanan Tian
Journal:  BMC Bioinformatics       Date:  2009-10-26       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.