FunChIP: an R/Bioconductor package for functional classification of ChIP-seq shapes

No abstract is available for this paper.

• Publication year

  2017

• Venue

  Bioinform.

• Publication date

  2017-08-15

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.1093/bioinformatics/btx201PMID 28398543
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Peak shape clustering reveals biological insights

  2015influential reference
• Functional Data Analysis of Amplitude and Phase Variation

  2015cited by this paper
• Genome-wide analysis of p53 transcriptional programs in B cells upon exposure to genotoxic stress in vivo

  2015cited by this paper
• Analysis of AneuRisk65 data: $k$-mean alignment

  2014cited by this paper
• Analysis of proteomics data: Block k-mean alignment

  2014cited by this paper
• Analysis of spike train data: An application of $k$-mean alignment

  2014cited by this paper
• Selective transcriptional regulation by Myc in cellular growth control and lymphomagenesis

  2014cited by this paper
• Unscrambling butterfly oogenesis

  2013cited by this paper
• The MeDiChISeq ChIP-seq deconvolution package

  2013cited by this paper
• Location-Specific Responses to Thermal Stress in Larvae of the Reef-Building Coral Montastraea faveolata

  2010cited by this paper
• Evaluation of Algorithm Performance in ChIP-Seq Peak Detection

  2010cited by this paper
• K-mean Alignment for Curve Clustering

  2010cited by this paper
• On the definition of phase and amplitude variability in functional data analysis

  2009cited by this paper
• PICS: Probabilistic Inference for ChIP‐seq

  2009cited by this paper
• Model-based Analysis of ChIP-Seq (MACS)

  2008cited by this paper
• Quantifying similarity between motifs

  2007cited by this paper
• Bioconductor: open software development for computational biology and bioinformatics

  2004cited by this paper
• Fitting a Mixture Model By Expectation Maximization To Discover Motifs In Biopolymer

  1994cited by this paper
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis

  1987cited by this paper
• BIOINFORMATICS ORIGINAL PAPER

  year unknowninfluential reference

• Image Representational Path of Regional Cultural and Creative Products Based on Genetic Algorithm

  2022cites this paper
• Expression of E93 provides an instructive cue to control dynamic enhancer activity and chromatin accessibility during development

  2020influential citation
• The temporal transcription factor E93 controls dynamic enhancer activity and chromatin accessibility during development

  2019influential citation
• StoatyDive: Evaluation and classification of peak profiles for sequencing data

  2019cites this paper
• Functional data analysis for computational biology

  2019cites this paper
• Genome analysis Functional data analysis for computational biology

  2019cites this paper
• IWTomics: testing high‐resolution sequence‐based ‘Omics' data at multiple locations and scales

  2018cites this paper