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Items: 1 to 20 of 94

1.

A ChIP-Seq benchmark shows that sequence conservation mainly improves detection of strong transcription factor binding sites.

Håndstad T, Rye MB, Drabløs F, Sætrom P.

PLoS One. 2011 Apr 14;6(4):e18430. doi: 10.1371/journal.pone.0018430.

2.

Integrating genomic data to predict transcription factor binding.

Holloway DT, Kon M, DeLisi C.

Genome Inform. 2005;16(1):83-94.

PMID:
16362910
3.

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.

4.

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.

5.

Improving analysis of transcription factor binding sites within ChIP-Seq data based on topological motif enrichment.

Worsley Hunt R, Mathelier A, Del Peso L, Wasserman WW.

BMC Genomics. 2014 Jun 13;15:472. doi: 10.1186/1471-2164-15-472.

6.

On the detection and refinement of transcription factor binding sites using ChIP-Seq data.

Hu M, Yu J, Taylor JM, Chinnaiyan AM, Qin ZS.

Nucleic Acids Res. 2010 Apr;38(7):2154-67. doi: 10.1093/nar/gkp1180. Epub 2010 Jan 6.

7.

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.

8.

Identification of transcription factor binding sites derived from transposable element sequences using ChIP-seq.

Conley AB, Jordan IK.

Methods Mol Biol. 2010;674:225-40. doi: 10.1007/978-1-60761-854-6_14.

PMID:
20827595
9.

Evolutionary conservation of zinc finger transcription factor binding sites in promoters of genes co-expressed with WT1 in prostate cancer.

Eisermann K, Tandon S, Bazarov A, Brett A, Fraizer G, Piontkivska H.

BMC Genomics. 2008 Jul 16;9:337. doi: 10.1186/1471-2164-9-337.

10.
11.

MotEvo: integrated Bayesian probabilistic methods for inferring regulatory sites and motifs on multiple alignments of DNA sequences.

Arnold P, Erb I, Pachkov M, Molina N, van Nimwegen E.

Bioinformatics. 2012 Feb 15;28(4):487-94. doi: 10.1093/bioinformatics/btr695.

PMID:
22334039
12.

A manually curated ChIP-seq benchmark demonstrates room for improvement in current peak-finder programs.

Rye MB, Sætrom P, Drabløs F.

Nucleic Acids Res. 2011 Mar;39(4):e25. doi: 10.1093/nar/gkq1187. Epub 2010 Nov 26.

13.

Exploring conservation of transcription factor binding sites with CONREAL.

Berezikov E, Guryev V, Cuppen E.

Methods Mol Biol. 2007;395:437-48.

PMID:
17993690
14.

A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments.

Laajala TD, Raghav S, Tuomela S, Lahesmaa R, Aittokallio T, Elo LL.

BMC Genomics. 2009 Dec 18;10:618. doi: 10.1186/1471-2164-10-618.

15.

De-novo discovery of differentially abundant transcription factor binding sites including their positional preference.

Keilwagen J, Grau J, Paponov IA, Posch S, Strickert M, Grosse I.

PLoS Comput Biol. 2011 Feb 10;7(2):e1001070. doi: 10.1371/journal.pcbi.1001070. Erratum in: PLoS Comput Biol. 2011 Oct;7(10). doi: 10.1371/annotation/a0b541dc-472b-4076-a435-499ce9519335.

16.

Clustered ChIP-Seq-defined transcription factor binding sites and histone modifications map distinct classes of regulatory elements.

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

BMC Biol. 2011 Nov 24;9:80. doi: 10.1186/1741-7007-9-80.

17.

An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.

Cheng CY, Chu CH, Hsu HW, Hsu FR, Tang CY, Wang WC, Kung HJ, Chang PC.

BMC Genomics. 2014;15 Suppl 1:S1. doi: 10.1186/1471-2164-15-S1-S1. Epub 2014 Jan 24.

18.

Application of experimentally verified transcription factor binding sites models for computational analysis of ChIP-Seq data.

Levitsky VG, Kulakovskiy IV, Ershov NI, Oshchepkov DY, Makeev VJ, Hodgman TC, Merkulova TI.

BMC Genomics. 2014 Jan 29;15:80. doi: 10.1186/1471-2164-15-80.

19.

CTF: a CRF-based transcription factor binding sites finding system.

He Y, Zhang Y, Zheng G, Wei C.

BMC Genomics. 2012;13 Suppl 8:S18. doi: 10.1186/1471-2164-13-S8-S18. Epub 2012 Dec 17.

20.

Optimally choosing PWM motif databases and sequence scanning approaches based on ChIP-seq data.

Dabrowski M, Dojer N, Krystkowiak I, Kaminska B, Wilczynski B.

BMC Bioinformatics. 2015 May 1;16:140. doi: 10.1186/s12859-015-0573-5.

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