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Items: 1 to 20 of 155

1.

Denoising genome-wide histone ChIP-seq with convolutional neural networks.

Koh PW, Pierson E, Kundaje A.

Bioinformatics. 2017 Jul 15;33(14):i225-i233. doi: 10.1093/bioinformatics/btx243.

2.

cChIP-seq: a robust small-scale method for investigation of histone modifications.

Valensisi C, Liao JL, Andrus C, Battle SL, Hawkins RD.

BMC Genomics. 2015 Dec 21;16:1083. doi: 10.1186/s12864-015-2285-7.

3.

MAPS: Model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments.

Juric I, Yu M, Abnousi A, Raviram R, Fang R, Zhao Y, Zhang Y, Qiu Y, Yang Y, Li Y, Ren B, Hu M.

PLoS Comput Biol. 2019 Apr 15;15(4):e1006982. doi: 10.1371/journal.pcbi.1006982. eCollection 2019 Apr.

4.

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.

5.

Sensitive and robust assessment of ChIP-seq read distribution using a strand-shift profile.

Nakato R, Shirahige K.

Bioinformatics. 2018 Jul 15;34(14):2356-2363. doi: 10.1093/bioinformatics/bty137.

PMID:
29528371
6.

ChIP-Seq Analysis in Neurospora crassa.

Ferraro AR, Lewis ZA.

Methods Mol Biol. 2018;1775:241-250. doi: 10.1007/978-1-4939-7804-5_19.

PMID:
29876822
7.

Software for rapid time dependent ChIP-sequencing analysis (TDCA).

Myschyshyn M, Farren-Dai M, Chuang TJ, Vocadlo D.

BMC Bioinformatics. 2017 Nov 25;18(1):521. doi: 10.1186/s12859-017-1936-x.

8.

Preparation of Low-Input and Ligation-Free ChIP-seq Libraries Using Template-Switching Technology.

Bolduc N, Lehman AP, Farmer A.

Curr Protoc Mol Biol. 2016 Oct 10;116:7.28.1-7.28.26. doi: 10.1002/cpmb.24.

PMID:
27723085
9.

ChIP-chip versus ChIP-seq: lessons for experimental design and data analysis.

Ho JW, Bishop E, Karchenko PV, Nègre N, White KP, Park PJ.

BMC Genomics. 2011 Feb 28;12:134. doi: 10.1186/1471-2164-12-134.

10.

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.

11.

A novel statistical method for quantitative comparison of multiple ChIP-seq datasets.

Chen L, Wang C, Qin ZS, Wu H.

Bioinformatics. 2015 Jun 15;31(12):1889-96. doi: 10.1093/bioinformatics/btv094. Epub 2015 Feb 13.

12.

fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

Madrigal P.

Bioinformatics. 2017 Mar 1;33(5):746-748. doi: 10.1093/bioinformatics/btw724.

13.

annoPeak: a web application to annotate and visualize peaks from ChIP-seq/ChIP-exo-seq.

Tang X, Srivastava A, Liu H, Machiraju R, Huang K, Leone G.

Bioinformatics. 2017 May 15;33(10):1570-1571. doi: 10.1093/bioinformatics/btx016. Erratum in: Bioinformatics. 2018 Aug 15;34(16):2879.

14.

Ritornello: high fidelity control-free chromatin immunoprecipitation peak calling.

Stanton KP, Jin J, Lederman RR, Weissman SM, Kluger Y.

Nucleic Acids Res. 2017 Dec 1;45(21):e173. doi: 10.1093/nar/gkx799.

15.

Pathology tissue-chromatin immunoprecipitation, coupled with high-throughput sequencing, allows the epigenetic profiling of patient samples.

Fanelli M, Amatori S, Barozzi I, Soncini M, Dal Zuffo R, Bucci G, Capra M, Quarto M, Dellino GI, Mercurio C, Alcalay M, Viale G, Pelicci PG, Minucci S.

Proc Natl Acad Sci U S A. 2010 Dec 14;107(50):21535-40. doi: 10.1073/pnas.1007647107. Epub 2010 Nov 24.

16.

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues.

Terranova C, Tang M, Orouji E, Maitituoheti M, Raman A, Amin S, Liu Z, Rai K.

J Vis Exp. 2018 Apr 5;(134). doi: 10.3791/56972.

17.

Exploiting Chromatin Biology to Understand Immunology.

Johnson JL, Vahedi G.

Methods Enzymol. 2016;574:365-383. doi: 10.1016/bs.mie.2016.03.016. Epub 2016 Apr 27.

PMID:
27423869
18.

Chromatin Preparation and Chromatin Immuno-precipitation from Drosophila Embryos.

Löser E, Latreille D, Iovino N.

Methods Mol Biol. 2016;1480:23-36. doi: 10.1007/978-1-4939-6380-5_3. Erratum in: Methods Mol Biol. 2016;1480:E1.

PMID:
27659972
19.

CHANCE: comprehensive software for quality control and validation of ChIP-seq data.

Diaz A, Nellore A, Song JS.

Genome Biol. 2012 Oct 15;13(10):R98. doi: 10.1186/gb-2012-13-10-r98.

20.

ChIPWig: a random access-enabling lossless and lossy compression method for ChIP-seq data.

Ravanmehr V, Kim M, Wang Z, Milenkovic O.

Bioinformatics. 2018 Mar 15;34(6):911-919. doi: 10.1093/bioinformatics/btx685.

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