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Items: 1 to 20 of 292

1.

TIP: a probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles.

Cheng C, Min R, Gerstein M.

Bioinformatics. 2011 Dec 1;27(23):3221-7. doi: 10.1093/bioinformatics/btr552. Epub 2011 Oct 29.

2.

A biophysical model for analysis of transcription factor interaction and binding site arrangement from genome-wide binding data.

He X, Chen CC, Hong F, Fang F, Sinha S, Ng HH, Zhong S.

PLoS One. 2009 Dec 1;4(12):e8155. doi: 10.1371/journal.pone.0008155.

3.

TF Target Mapper: a BLAST search tool for the identification of Transcription Factor target genes.

Horsman S, Moorhouse MJ, de Jager VC, van der Spek P, Grosveld F, Strouboulis J, Katsantoni EZ.

BMC Bioinformatics. 2006 Mar 8;7:120.

4.

Cell-type specificity of ChIP-predicted transcription factor binding sites.

Håndstad T, Rye M, Močnik R, Drabløs F, Sætrom P.

BMC Genomics. 2012 Aug 3;13:372. doi: 10.1186/1471-2164-13-372.

5.

Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data.

Zhang Y, Xuan J, de los Reyes BG, Clarke R, Ressom HW.

BMC Bioinformatics. 2008 Apr 21;9:203. doi: 10.1186/1471-2105-9-203.

6.

Positional distribution of human transcription factor binding sites.

Koudritsky M, Domany E.

Nucleic Acids Res. 2008 Dec;36(21):6795-805. doi: 10.1093/nar/gkn752. Epub 2008 Oct 25.

7.

Relationship between estrogen receptor alpha location and gene induction reveals the importance of downstream sites and cofactors.

Parisi F, Sonderegger B, Wirapati P, Delorenzi M, Naef F.

BMC Genomics. 2009 Aug 18;10:381. doi: 10.1186/1471-2164-10-381.

8.

De novo motif identification improves the accuracy of predicting transcription factor binding sites in ChIP-Seq data analysis.

Boeva V, Surdez D, Guillon N, Tirode F, Fejes AP, Delattre O, Barillot E.

Nucleic Acids Res. 2010 Jun;38(11):e126. doi: 10.1093/nar/gkq217. Epub 2010 Apr 7.

9.

iTAR: a web server for identifying target genes of transcription factors using ChIP-seq or ChIP-chip data.

Yang CC, Andrews EH, Chen MH, Wang WY, Chen JJ, Gerstein M, Liu CC, Cheng C.

BMC Genomics. 2016 Aug 12;17(1):632. doi: 10.1186/s12864-016-2963-0.

10.

ChIPXpress: using publicly available gene expression data to improve ChIP-seq and ChIP-chip target gene ranking.

Wu G, Ji H.

BMC Bioinformatics. 2013 Jun 10;14:188. doi: 10.1186/1471-2105-14-188.

11.
12.

PscanChIP: Finding over-represented transcription factor-binding site motifs and their correlations in sequences from ChIP-Seq experiments.

Zambelli F, Pesole G, Pavesi G.

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W535-43. doi: 10.1093/nar/gkt448. Epub 2013 Jun 7.

13.

De novo motif discovery facilitates identification of interactions between transcription factors in Saccharomyces cerevisiae.

Chen MJ, Chou LC, Hsieh TT, Lee DD, Liu KW, Yu CY, Oyang YJ, Tsai HK, Chen CY.

Bioinformatics. 2012 Mar 1;28(5):701-8. doi: 10.1093/bioinformatics/bts002. Epub 2012 Jan 11.

PMID:
22238267
14.

Assessing computational methods for transcription factor target gene identification based on ChIP-seq data.

Sikora-Wohlfeld W, Ackermann M, Christodoulou EG, Singaravelu K, Beyer A.

PLoS Comput Biol. 2013;9(11):e1003342. doi: 10.1371/journal.pcbi.1003342. Epub 2013 Nov 21.

15.

Relative avidity, specificity, and sensitivity of transcription factor-DNA binding in genome-scale experiments.

Kuznetsov VA.

Methods Mol Biol. 2009;563:15-50. doi: 10.1007/978-1-60761-175-2_2.

PMID:
19597778
16.

Chromatin immunoprecipitation and multiplex sequencing (ChIP-Seq) to identify global transcription factor binding sites in the nematode Caenorhabditis elegans.

Brdlik CM, Niu W, Snyder M.

Methods Enzymol. 2014;539:89-111. doi: 10.1016/B978-0-12-420120-0.00007-4.

PMID:
24581441
17.

ChIP-Array: combinatory analysis of ChIP-seq/chip and microarray gene expression data to discover direct/indirect targets of a transcription factor.

Qin J, Li MJ, Wang P, Zhang MQ, Wang J.

Nucleic Acids Res. 2011 Jul;39(Web Server issue):W430-6. doi: 10.1093/nar/gkr332. Epub 2011 May 17.

18.

High resolution models of transcription factor-DNA affinities improve in vitro and in vivo binding predictions.

Agius P, Arvey A, Chang W, Noble WS, Leslie C.

PLoS Comput Biol. 2010 Sep 9;6(9). pii: e1000916. doi: 10.1371/journal.pcbi.1000916.

19.

Characterization of genome-wide binding of NF-κB in TNFα-stimulated HeLa cells.

Xing Y, Yang Y, Zhou F, Wang J.

Gene. 2013 Sep 10;526(2):142-9. doi: 10.1016/j.gene.2013.05.001. Epub 2013 May 17.

PMID:
23688556
20.

Statistics of protein-DNA binding and the total number of binding sites for a transcription factor in the mammalian genome.

Kuznetsov VA, Singh O, Jenjaroenpun P.

BMC Genomics. 2010 Feb 10;11 Suppl 1:S12. doi: 10.1186/1471-2164-11-S1-S12.

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