These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

145 related articles for article (PubMed ID: 21471015)

  • 1. DIME: R-package for identifying differential ChIP-seq based on an ensemble of mixture models.
    Taslim C; Huang T; Lin S
    Bioinformatics; 2011 Jun; 27(11):1569-70. PubMed ID: 21471015
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comparative study on ChIP-seq data: normalization and binding pattern characterization.
    Taslim C; Wu J; Yan P; Singer G; Parvin J; Huang T; Lin S; Huang K
    Bioinformatics; 2009 Sep; 25(18):2334-40. PubMed ID: 19561022
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Empirical methods for controlling false positives and estimating confidence in ChIP-Seq peaks.
    Nix DA; Courdy SJ; Boucher KM
    BMC Bioinformatics; 2008 Dec; 9():523. PubMed ID: 19061503
    [TBL] [Abstract][Full Text] [Related]  

  • 4. ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data.
    Zhu LJ; Gazin C; Lawson ND; Pagès H; Lin SM; Lapointe DS; Green MR
    BMC Bioinformatics; 2010 May; 11():237. PubMed ID: 20459804
    [TBL] [Abstract][Full Text] [Related]  

  • 5. BayesPeak--an R package for analysing ChIP-seq data.
    Cairns J; Spyrou C; Stark R; Smith ML; Lynch AG; Tavaré S
    Bioinformatics; 2011 Mar; 27(5):713-4. PubMed ID: 21245054
    [TBL] [Abstract][Full Text] [Related]  

  • 6. rMAT--an R/Bioconductor package for analyzing ChIP-chip experiments.
    Droit A; Cheung C; Gottardo R
    Bioinformatics; 2010 Mar; 26(5):678-9. PubMed ID: 20089513
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. A novel statistical method for quantitative comparison of multiple ChIP-seq datasets.
    Chen L; Wang C; Qin ZS; Wu H
    Bioinformatics; 2015 Jun; 31(12):1889-96. PubMed ID: 25682068
    [TBL] [Abstract][Full Text] [Related]  

  • 9. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization.
    Yu G; Wang LG; He QY
    Bioinformatics; 2015 Jul; 31(14):2382-3. PubMed ID: 25765347
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. GMD: measuring the distance between histograms with applications on high-throughput sequencing reads.
    Zhao X; Sandelin A
    Bioinformatics; 2012 Apr; 28(8):1164-5. PubMed ID: 22345619
    [TBL] [Abstract][Full Text] [Related]  

  • 12. diffReps: detecting differential chromatin modification sites from ChIP-seq data with biological replicates.
    Shen L; Shao NY; Liu X; Maze I; Feng J; Nestler EJ
    PLoS One; 2013; 8(6):e65598. PubMed ID: 23762400
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A penalized Bayesian approach to predicting sparse protein-DNA binding landscapes.
    Levinson M; Zhou Q
    Bioinformatics; 2014 Mar; 30(5):636-43. PubMed ID: 24115169
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Accounting for immunoprecipitation efficiencies in the statistical analysis of ChIP-seq data.
    Bao Y; Vinciotti V; Wit E; 't Hoen PA
    BMC Bioinformatics; 2013 May; 14():169. PubMed ID: 23721376
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Optimizing detection of transcription factor-binding sites in ChIP-seq experiments.
    Kallio A; Elo LL
    Methods Mol Biol; 2013; 1038():181-91. PubMed ID: 23872976
    [TBL] [Abstract][Full Text] [Related]  

  • 16. F-Seq: a feature density estimator for high-throughput sequence tags.
    Boyle AP; Guinney J; Crawford GE; Furey TS
    Bioinformatics; 2008 Nov; 24(21):2537-8. PubMed ID: 18784119
    [TBL] [Abstract][Full Text] [Related]  

  • 17. PeakRanger: a cloud-enabled peak caller for ChIP-seq data.
    Feng X; Grossman R; Stein L
    BMC Bioinformatics; 2011 May; 12():139. PubMed ID: 21554709
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A signal-noise model for significance analysis of ChIP-seq with negative control.
    Xu H; Handoko L; Wei X; Ye C; Sheng J; Wei CL; Lin F; Sung WK
    Bioinformatics; 2010 May; 26(9):1199-204. PubMed ID: 20371496
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Shape-based peak identification for ChIP-Seq.
    Hower V; Evans SN; Pachter L
    BMC Bioinformatics; 2011 Jan; 12():15. PubMed ID: 21226895
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Analyzing ChIP-seq data: preprocessing, normalization, differential identification, and binding pattern characterization.
    Taslim C; Huang K; Huang T; Lin S
    Methods Mol Biol; 2012; 802():275-91. PubMed ID: 22130887
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.