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Items: 1 to 20 of 106

1.

Using MACS to identify peaks from ChIP-Seq data.

Feng J, Liu T, Zhang Y.

Curr Protoc Bioinformatics. 2011 Jun;Chapter 2:Unit 2.14. doi: 10.1002/0471250953.bi0214s34.

2.
3.

Identifying ChIP-seq enrichment using MACS.

Feng J, Liu T, Qin B, Zhang Y, Liu XS.

Nat Protoc. 2012 Sep;7(9):1728-40. doi: 10.1038/nprot.2012.101. Epub 2012 Aug 30.

4.

HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data.

Qin ZS, Yu J, Shen J, Maher CA, Hu M, Kalyana-Sundaram S, Yu J, Chinnaiyan AM.

BMC Bioinformatics. 2010 Jul 2;11:369. doi: 10.1186/1471-2105-11-369.

5.

Computational analysis of ChIP-seq data.

Ji H.

Methods Mol Biol. 2010;674:143-59. doi: 10.1007/978-1-60761-854-6_9.

PMID:
20827590
6.

dPeak: high resolution identification of transcription factor binding sites from PET and SET ChIP-Seq data.

Chung D, Park D, Myers K, Grass J, Kiley P, Landick R, Keleş S.

PLoS Comput Biol. 2013;9(10):e1003246. doi: 10.1371/journal.pcbi.1003246. Epub 2013 Oct 17.

7.

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.

8.

The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding.

Kornacker K, Rye MB, Håndstad T, Drabløs F.

BMC Bioinformatics. 2012 Jul 24;13:176. doi: 10.1186/1471-2105-13-176.

9.

Design and analysis of ChIP-seq experiments for DNA-binding proteins.

Kharchenko PV, Tolstorukov MY, Park PJ.

Nat Biotechnol. 2008 Dec;26(12):1351-9. doi: 10.1038/nbt.1508. Epub 2008 Nov 16.

10.

Using combined evidence from replicates to evaluate ChIP-seq peaks.

Jalili V, Matteucci M, Masseroli M, Morelli MJ.

Bioinformatics. 2015 Sep 1;31(17):2761-9. doi: 10.1093/bioinformatics/btv293. Epub 2015 May 7.

PMID:
25957351
11.

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.

12.

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.

13.

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.

14.

Discovering transcription factor binding sites in highly repetitive regions of genomes with multi-read analysis of ChIP-Seq data.

Chung D, Kuan PF, Li B, Sanalkumar R, Liang K, Bresnick EH, Dewey C, Keleş S.

PLoS Comput Biol. 2011 Jul;7(7):e1002111. doi: 10.1371/journal.pcbi.1002111. Epub 2011 Jul 14.

15.

The analysis of ChIP-Seq data.

Ma W, Wong WH.

Methods Enzymol. 2011;497:51-73. doi: 10.1016/B978-0-12-385075-1.00003-2.

PMID:
21601082
16.

QChIPat: a quantitative method to identify distinct binding patterns for two biological ChIP-seq samples in different experimental conditions.

Liu B, Yi J, Sv A, Lan X, Ma Y, Huang TH, Leone G, Jin VX.

BMC Genomics. 2013;14 Suppl 8:S3. doi: 10.1186/1471-2164-14-S8-S3. Epub 2013 Dec 9.

17.

Is this the right normalization? A diagnostic tool for ChIP-seq normalization.

Angelini C, Heller R, Volkinshtein R, Yekutieli D.

BMC Bioinformatics. 2015 May 9;16:150. doi: 10.1186/s12859-015-0579-z.

18.

A Fast Cluster Motif Finding Algorithm for ChIP-Seq Data Sets.

Zhang Y, Wang P.

Biomed Res Int. 2015;2015:218068. doi: 10.1155/2015/218068. Epub 2015 Jul 5.

19.

BayesPeak: Bayesian analysis of ChIP-seq data.

Spyrou C, Stark R, Lynch AG, Tavaré S.

BMC Bioinformatics. 2009 Sep 21;10:299. doi: 10.1186/1471-2105-10-299.

20.

ChIPseqR: analysis of ChIP-seq experiments.

Humburg P, Helliwell CA, Bulger D, Stone G.

BMC Bioinformatics. 2011 Jan 31;12:39. doi: 10.1186/1471-2105-12-39.

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