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Items: 1 to 20 of 75

1.

ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline.

Qin Q, Mei S, Wu Q, Sun H, Li L, Taing L, Chen S, Li F, Liu T, Zang C, Xu H, Chen Y, Meyer CA, Zhang Y, Brown M, Long HW, Liu XS.

BMC Bioinformatics. 2016 Oct 3;17(1):404.

2.

Wnt-signalling pathways and microRNAs network in carcinogenesis: experimental and bioinformatics approaches.

Onyido EK, Sweeney E, Nateri AS.

Mol Cancer. 2016 Sep 2;15(1):56. doi: 10.1186/s12943-016-0541-3. Review.

3.

An Integrated Analysis of MicroRNA and mRNA Expression Profiles to Identify RNA Expression Signatures in Lambskin Hair Follicles in Hu Sheep.

Lv X, Sun W, Yin J, Ni R, Su R, Wang Q, Gao W, Bao J, Yu J, Wang L, Chen L.

PLoS One. 2016 Jul 12;11(7):e0157463. doi: 10.1371/journal.pone.0157463. eCollection 2016.

4.

Reusable, extensible, and modifiable R scripts and Kepler workflows for comprehensive single set ChIP-seq analysis.

Cormier N, Kolisnik T, Bieda M.

BMC Bioinformatics. 2016 Jul 5;17(1):270. doi: 10.1186/s12859-016-1125-3.

5.

Misregulation of Alternative Splicing in a Mouse Model of Rett Syndrome.

Li R, Dong Q, Yuan X, Zeng X, Gao Y, Chiao C, Li H, Zhao X, Keles S, Wang Z, Chang Q.

PLoS Genet. 2016 Jun 28;12(6):e1006129. doi: 10.1371/journal.pgen.1006129. eCollection 2016 Jun.

6.

Features that define the best ChIP-seq peak calling algorithms.

Thomas R, Thomas S, Holloway AK, Pollard KS.

Brief Bioinform. 2017 May 1;18(3):441-450. doi: 10.1093/bib/bbw035.

7.

Effects on the transcriptome upon deletion of a distal element cannot be predicted by the size of the H3K27Ac peak in human cells.

Tak YG, Hung Y, Yao L, Grimmer MR, Do A, Bhakta MS, O'Geen H, Segal DJ, Farnham PJ.

Nucleic Acids Res. 2016 May 19;44(9):4123-33. doi: 10.1093/nar/gkv1530. Epub 2016 Jan 6.

8.

Global transcriptome and chromatin occupancy analysis reveal the short isoform of GATA1 is deficient for erythroid specification and gene expression.

Chlon TM, McNulty M, Goldenson B, Rosinski A, Crispino JD.

Haematologica. 2015 May;100(5):575-84. doi: 10.3324/haematol.2014.112714. Epub 2015 Feb 14.

9.

A novel role for the Pol I transcription factor UBTF in maintaining genome stability through the regulation of highly transcribed Pol II genes.

Sanij E, Diesch J, Lesmana A, Poortinga G, Hein N, Lidgerwood G, Cameron DP, Ellul J, Goodall GJ, Wong LH, Dhillon AS, Hamdane N, Rothblum LI, Pearson RB, Haviv I, Moss T, Hannan RD.

Genome Res. 2015 Feb;25(2):201-12. doi: 10.1101/gr.176115.114. Epub 2014 Dec 1.

10.

In silico pooling of ChIP-seq control experiments.

Sun G, Srinivasan R, Lopez-Anido C, Hung HA, Svaren J, Keleş S.

PLoS One. 2014 Nov 7;9(11):e109691. doi: 10.1371/journal.pone.0109691. eCollection 2014.

11.

Functional annotation of colon cancer risk SNPs.

Yao L, Tak YG, Berman BP, Farnham PJ.

Nat Commun. 2014 Sep 30;5:5114. doi: 10.1038/ncomms6114.

12.

Global loss of DNA methylation uncovers intronic enhancers in genes showing expression changes.

Blattler A, Yao L, Witt H, Guo Y, Nicolet CM, Berman BP, Farnham PJ.

Genome Biol. 2014 Sep 20;15(9):469. doi: 10.1186/s13059-014-0469-0.

13.

Global analysis of transcription factor-binding sites in yeast using ChIP-Seq.

Lefrançois P, Gallagher JE, Snyder M.

Methods Mol Biol. 2014;1205:231-55. doi: 10.1007/978-1-4939-1363-3_15.

14.

Bipartite recognition of DNA by TCF/Pangolin is remarkably flexible and contributes to transcriptional responsiveness and tissue specificity of wingless signaling.

Archbold HC, Broussard C, Chang MV, Cadigan KM.

PLoS Genet. 2014 Sep 4;10(9):e1004591. doi: 10.1371/journal.pgen.1004591. eCollection 2014 Sep.

15.

Analysis of an artificial zinc finger epigenetic modulator: widespread binding but limited regulation.

Grimmer MR, Stolzenburg S, Ford E, Lister R, Blancafort P, Farnham PJ.

Nucleic Acids Res. 2014;42(16):10856-68. doi: 10.1093/nar/gku708. Epub 2014 Aug 13.

16.

Global analysis of ZNF217 chromatin occupancy in the breast cancer cell genome reveals an association with ERalpha.

Frietze S, O'Geen H, Littlepage LE, Simion C, Sweeney CA, Farnham PJ, Krig SR.

BMC Genomics. 2014 Jun 24;15:520. doi: 10.1186/1471-2164-15-520.

17.

OccuPeak: ChIP-Seq peak calling based on internal background modelling.

de Boer BA, van Duijvenboden K, van den Boogaard M, Christoffels VM, Barnett P, Ruijter JM.

PLoS One. 2014 Jun 17;9(6):e99844. doi: 10.1371/journal.pone.0099844. eCollection 2014.

18.

PePr: a peak-calling prioritization pipeline to identify consistent or differential peaks from replicated ChIP-Seq data.

Zhang Y, Lin YH, Johnson TD, Rozek LS, Sartor MA.

Bioinformatics. 2014 Sep 15;30(18):2568-75. doi: 10.1093/bioinformatics/btu372. Epub 2014 Jun 3.

19.

The spatiotemporal program of DNA replication is associated with specific combinations of chromatin marks in human cells.

Picard F, Cadoret JC, Audit B, Arneodo A, Alberti A, Battail C, Duret L, Prioleau MN.

PLoS Genet. 2014 May 1;10(5):e1004282. doi: 10.1371/journal.pgen.1004282. eCollection 2014 May.

20.

Statistical Issues in the Analysis of ChIP-Seq and RNA-Seq Data.

Ghosh D, Qin ZS.

Genes (Basel). 2010 Sep 27;1(2):317-34. doi: 10.3390/genes1020317.

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