306 related articles for article (PubMed ID: 21633945)
1. Using MACS to identify peaks from ChIP-Seq data.
Feng J; Liu T; Zhang Y
Curr Protoc Bioinformatics; 2011 Jun; Chapter 2():2.14.1-2.14.14. PubMed ID: 21633945
[TBL] [Abstract][Full Text] [Related]
2. Use model-based Analysis of ChIP-Seq (MACS) to analyze short reads generated by sequencing protein-DNA interactions in embryonic stem cells.
Liu T
Methods Mol Biol; 2014; 1150():81-95. PubMed ID: 24743991
[TBL] [Abstract][Full Text] [Related]
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. PubMed ID: 22936215
[TBL] [Abstract][Full Text] [Related]
4. 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. PubMed ID: 24146601
[TBL] [Abstract][Full Text] [Related]
5. FisherMP: fully parallel algorithm for detecting combinatorial motifs from large ChIP-seq datasets.
Zhang S; Liang Y; Wang X; Su Z; Chen Y
DNA Res; 2019 Jun; 26(3):231-242. PubMed ID: 30957858
[TBL] [Abstract][Full Text] [Related]
6. 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; 10():618. PubMed ID: 20017957
[TBL] [Abstract][Full Text] [Related]
7. Computational analysis of ChIP-seq data.
Ji H
Methods Mol Biol; 2010; 674():143-59. PubMed ID: 20827590
[TBL] [Abstract][Full Text] [Related]
8. 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; 11():369. PubMed ID: 20598134
[TBL] [Abstract][Full Text] [Related]
9. Role of ChIP-seq in the discovery of transcription factor binding sites, differential gene regulation mechanism, epigenetic marks and beyond.
Mundade R; Ozer HG; Wei H; Prabhu L; Lu T
Cell Cycle; 2014; 13(18):2847-52. PubMed ID: 25486472
[TBL] [Abstract][Full Text] [Related]
10. 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. PubMed ID: 19029915
[TBL] [Abstract][Full Text] [Related]
11. Peak-Finding Algorithms.
Hung JH; Weng Z
Cold Spring Harb Protoc; 2017 Mar; 2017(3):. PubMed ID: 27574196
[TBL] [Abstract][Full Text] [Related]
12. The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding.
Kornacker K; Rye MB; Håndstad T; Drabløs F
BMC Bioinformatics; 2012 Jul; 13():176. PubMed ID: 22827163
[TBL] [Abstract][Full Text] [Related]
13. Using combined evidence from replicates to evaluate ChIP-seq peaks.
Jalili V; Matteucci M; Masseroli M; Morelli MJ
Bioinformatics; 2015 Sep; 31(17):2761-9. PubMed ID: 25957351
[TBL] [Abstract][Full Text] [Related]
14. AIControl: replacing matched control experiments with machine learning improves ChIP-seq peak identification.
Hiranuma N; Lundberg SM; Lee SI
Nucleic Acids Res; 2019 Jun; 47(10):e58. PubMed ID: 30869146
[TBL] [Abstract][Full Text] [Related]
15. Is this the right normalization? A diagnostic tool for ChIP-seq normalization.
Angelini C; Heller R; Volkinshtein R; Yekutieli D
BMC Bioinformatics; 2015 May; 16():150. PubMed ID: 25957089
[TBL] [Abstract][Full Text] [Related]
16. ChIPulate: A comprehensive ChIP-seq simulation pipeline.
Datta V; Hannenhalli S; Siddharthan R
PLoS Comput Biol; 2019 Mar; 15(3):e1006921. PubMed ID: 30897079
[TBL] [Abstract][Full Text] [Related]
17. The analysis of ChIP-Seq data.
Ma W; Wong WH
Methods Enzymol; 2011; 497():51-73. PubMed ID: 21601082
[TBL] [Abstract][Full Text] [Related]
18. 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(Suppl 8):S3. PubMed ID: 24564479
[TBL] [Abstract][Full Text] [Related]
19. 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; 15(1):472. PubMed ID: 24927817
[TBL] [Abstract][Full Text] [Related]
20. MotifGenie: a Python application for searching transcription factor binding sequences using ChIP-Seq datasets.
Oguztuzun C; Yasar P; Yavuz K; Muyan M; Can T
Bioinformatics; 2021 Nov; 37(22):4238-4239. PubMed ID: 33999190
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]