Hongkai Ji

Summary

Affiliation: Johns Hopkins Bloomberg School of Public Health
Country: USA

Publications

  1. pmc TileProbe: modeling tiling array probe effects using publicly available data
    Jennifer Toolan Judy
    Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Bioinformatics 25:2369-75. 2009
  2. pmc ChIP-PED enhances the analysis of ChIP-seq and ChIP-chip data
    George Wu
    Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Bioinformatics 29:1182-9. 2013
  3. pmc Differential principal component analysis of ChIP-seq
    Hongkai Ji
    Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
    Proc Natl Acad Sci U S A 110:6789-94. 2013
  4. doi request reprint Computational analysis of ChIP-seq data
    Hongkai Ji
    Department of Biostatistics, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
    Methods Mol Biol 674:143-59. 2010
  5. pmc Cell-type independent MYC target genes reveal a primordial signature involved in biomass accumulation
    Hongkai Ji
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
    PLoS ONE 6:e26057. 2011
  6. pmc ChIPXpress: using publicly available gene expression data to improve ChIP-seq and ChIP-chip target gene ranking
    George Wu
    Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA
    BMC Bioinformatics 14:188. 2013
  7. pmc Using CisGenome to analyze ChIP-chip and ChIP-seq data
    Hongkai Ji
    The Johns Hopkins University, Baltimore, Maryland, USA
    Curr Protoc Bioinformatics . 2011
  8. ncbi request reprint Gene set bagging for estimating the probability a statistically significant result will replicate
    Andrew E Jaffe
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore MD 21205, USA
    BMC Bioinformatics 14:360. 2013
  9. pmc iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets
    Yingying Wei
    Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, 615 North Wolfe StreetBaltimore, Maryland 21205, USA
    BMC Genomics 13:681. 2012
  10. pmc JAMIE: joint analysis of multiple ChIP-chip experiments
    Hao Wu
    Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205, USA
    Bioinformatics 26:1864-70. 2010

Collaborators

Detail Information

Publications15

  1. pmc TileProbe: modeling tiling array probe effects using publicly available data
    Jennifer Toolan Judy
    Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Bioinformatics 25:2369-75. 2009
    ..Although the MAT approach can be applied without control samples, residual probe effects continue to distort the true biological signals...
  2. pmc ChIP-PED enhances the analysis of ChIP-seq and ChIP-chip data
    George Wu
    Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Bioinformatics 29:1182-9. 2013
    ..Thus, standard ChIPx analyses primarily focus on analyzing data from one experiment, and the discoveries are restricted to a specific biological context...
  3. pmc Differential principal component analysis of ChIP-seq
    Hongkai Ji
    Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
    Proc Natl Acad Sci U S A 110:6789-94. 2013
    ..We demonstrate this approach through analyses of differential chromatin patterns at transcription factor binding sites and promoters as well as allele-specific protein-DNA interactions...
  4. doi request reprint Computational analysis of ChIP-seq data
    Hongkai Ji
    Department of Biostatistics, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
    Methods Mol Biol 674:143-59. 2010
    ..This chapter reviews basic characteristics of ChIP-seq data and introduces a computational procedure to identify protein-DNA interactions from ChIP-seq experiments...
  5. pmc Cell-type independent MYC target genes reveal a primordial signature involved in biomass accumulation
    Hongkai Ji
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
    PLoS ONE 6:e26057. 2011
    ..Annotation of this gene signature reveals Myc's primordial function in RNA processing, ribosome biogenesis and biomass accumulation as its key roles in cancer and stem cells...
  6. pmc ChIPXpress: using publicly available gene expression data to improve ChIP-seq and ChIP-chip target gene ranking
    George Wu
    Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA
    BMC Bioinformatics 14:188. 2013
    ..ChIPXpress is a novel method that improves upon this ChIPx-only ranking approach by integrating ChIPx data with large amounts of Publicly available gene Expression Data (PED)...
  7. pmc Using CisGenome to analyze ChIP-chip and ChIP-seq data
    Hongkai Ji
    The Johns Hopkins University, Baltimore, Maryland, USA
    Curr Protoc Bioinformatics . 2011
    ....
  8. ncbi request reprint Gene set bagging for estimating the probability a statistically significant result will replicate
    Andrew E Jaffe
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore MD 21205, USA
    BMC Bioinformatics 14:360. 2013
    ..Gene set bagging involves resampling the original high-throughput data, performing gene-set analysis on the resampled data, and confirming that biological categories replicate in the bagged samples...
  9. pmc iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets
    Yingying Wei
    Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, 615 North Wolfe StreetBaltimore, Maryland 21205, USA
    BMC Genomics 13:681. 2012
    ..However, detecting allelic imbalance from a single ChIP-seq dataset often has low statistical power since only sequence reads mapped to heterozygote SNPs are informative for discriminating two alleles...
  10. pmc JAMIE: joint analysis of multiple ChIP-chip experiments
    Hao Wu
    Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205, USA
    Bioinformatics 26:1864-70. 2010
    ..When multiple related ChIP-chip datasets are available, analyzing them jointly allows one to borrow information across datasets to improve peak detection. This is particularly useful for analyzing noisy datasets...
  11. pmc An integrated software system for analyzing ChIP-chip and ChIP-seq data
    Hongkai Ji
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, Maryland 21205, USA
    Nat Biotechnol 26:1293-300. 2008
    ....
  12. pmc hmChIP: a database and web server for exploring publicly available human and mouse ChIP-seq and ChIP-chip data
    Li Chen
    Department of Biostatistics, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Bioinformatics 27:1447-8. 2011
    ..The retrieved intensities can be used to cluster samples and genomic regions to facilitate exploration of combinatorial patterns, cell-type dependencies, and cross-sample variability of protein-DNA interactions...
  13. pmc Dynamics of regulatory networks in the developing mouse retina
    Woochang Hwang
    Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
    PLoS ONE 7:e46521. 2012
    ....
  14. pmc Construction of human activity-based phosphorylation networks
    Robert H Newman
    Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
    Mol Syst Biol 9:655. 2013
    ..Overall, these studies provide global insights into kinase-mediated signaling pathways and promise to advance our understanding of cellular signaling processes in humans...