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Items: 1 to 20 of 333

1.

MEME-ChIP: motif analysis of large DNA datasets.

Machanick P, Bailey TL.

Bioinformatics. 2011 Jun 15;27(12):1696-7. doi: 10.1093/bioinformatics/btr189. Epub 2011 Apr 12.

2.

DREME: motif discovery in transcription factor ChIP-seq data.

Bailey TL.

Bioinformatics. 2011 Jun 15;27(12):1653-9. doi: 10.1093/bioinformatics/btr261. Epub 2011 May 4.

3.

Inferring direct DNA binding from ChIP-seq.

Bailey TL, Machanick P.

Nucleic Acids Res. 2012 Sep 1;40(17):e128. Epub 2012 May 18.

4.

EXTREME: an online EM algorithm for motif discovery.

Quang D, Xie X.

Bioinformatics. 2014 Jun 15;30(12):1667-73. doi: 10.1093/bioinformatics/btu093. Epub 2014 Feb 14.

5.

Motif-based analysis of large nucleotide data sets using MEME-ChIP.

Ma W, Noble WS, Bailey TL.

Nat Protoc. 2014;9(6):1428-50. doi: 10.1038/nprot.2014.083. Epub 2014 May 22.

6.

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.

7.

MEME SUITE: tools for motif discovery and searching.

Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, Ren J, Li WW, Noble WS.

Nucleic Acids Res. 2009 Jul;37(Web Server issue):W202-8. doi: 10.1093/nar/gkp335. Epub 2009 May 20.

8.

Inferring transcription factor complexes from ChIP-seq data.

Whitington T, Frith MC, Johnson J, Bailey TL.

Nucleic Acids Res. 2011 Aug;39(15):e98. doi: 10.1093/nar/gkr341. Epub 2011 May 20.

9.

Differential motif enrichment analysis of paired ChIP-seq experiments.

Lesluyes T, Johnson J, Machanick P, Bailey TL.

BMC Genomics. 2014 Sep 2;15:752. doi: 10.1186/1471-2164-15-752.

10.

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.

11.

The value of position-specific priors in motif discovery using MEME.

Bailey TL, Bodén M, Whitington T, Machanick P.

BMC Bioinformatics. 2010 Apr 9;11:179. doi: 10.1186/1471-2105-11-179.

12.

COPS: detecting co-occurrence and spatial arrangement of transcription factor binding motifs in genome-wide datasets.

Ha N, Polychronidou M, Lohmann I.

PLoS One. 2012;7(12):e52055. doi: 10.1371/journal.pone.0052055. Epub 2012 Dec 18.

13.

SIOMICS: a novel approach for systematic identification of motifs in ChIP-seq data.

Ding J, Hu H, Li X.

Nucleic Acids Res. 2014 Mar;42(5):e35. doi: 10.1093/nar/gkt1288. Epub 2013 Dec 9.

14.

Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets.

Worsley Hunt R, Wasserman WW.

Genome Biol. 2014 Jul 29;15(7):412. doi: 10.1186/s13059-014-0412-4.

15.

MEME-LaB: motif analysis in clusters.

Brown P, Baxter L, Hickman R, Beynon J, Moore JD, Ott S.

Bioinformatics. 2013 Jul 1;29(13):1696-7. doi: 10.1093/bioinformatics/btt248. Epub 2013 May 16.

16.

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.

17.

A survey of motif finding Web tools for detecting binding site motifs in ChIP-Seq data.

Tran NT, Huang CH.

Biol Direct. 2014 Feb 20;9:4. doi: 10.1186/1745-6150-9-4. Review.

18.

RSAT peak-motifs: motif analysis in full-size ChIP-seq datasets.

Thomas-Chollier M, Herrmann C, Defrance M, Sand O, Thieffry D, van Helden J.

Nucleic Acids Res. 2012 Feb;40(4):e31. doi: 10.1093/nar/gkr1104. Epub 2011 Dec 8.

19.

LASAGNA: a novel algorithm for transcription factor binding site alignment.

Lee C, Huang CH.

BMC Bioinformatics. 2013 Mar 24;14:108. doi: 10.1186/1471-2105-14-108.

20.

CENTDIST: discovery of co-associated factors by motif distribution.

Zhang Z, Chang CW, Goh WL, Sung WK, Cheung E.

Nucleic Acids Res. 2011 Jul;39(Web Server issue):W391-9. doi: 10.1093/nar/gkr387. Epub 2011 May 20.

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